The Problem of “Mazbut” Concept in EU Progress Report For Turkey

Osmanlı’dan günümüze, devlet ve toplum ihtiyaçlarına göre değişen vakıf sistemi, zaman içerisinde oluşan kendine özgü kavramları ve uygulamaları günümüze kadar taşımıştır. Uluslararası düzeyde vakıf konusunda gündeme gelen sorunların sebebi, esasen tarihî süreç içerisinde özgün yapısıyla oluşa gelen vakıf sisteminin AB’nin vakıf sistemine uymamasıdır. Bu uyumsuzluğun somut örneklerinden biri olarak ortaya çıkan “mazbut vakıf” kavramının yanlış kullanımının önüne geçilmesi, Türk vakıf sisteminin sosyal ve tarihî bütünlüğü içinde ele alınması ile mümkün olacaktır. AB, Türkiye İlerleme Raporlarındaki “mazbut vakıf” sorunu, cemaat vakıflarına özgü gibi gösterilen, ancak uygulama ve kavram olarak Osmanlıdan günümüze gelmiş bugün hala devam eden bir uygulamanın, kavramın ve esasen yönetim şeklinin adıdır. “Mazbut vakıf” kavramının hukukî belge niteliği taşıyan Lozan tutanaklarındaki kullanış biçimi ile kullanılması, kavramın içerdiği anlam bütünlüğünü koruması açısından zorunluluk arz etmektedir

An Application of Using Elevator Systems for Peak Shaving in Smart Grid

Nüfusun ve enerjiye bağımlılığın artması ve fosil enerji kaynaklarının azalması, enerjinin daha verimli bir şekilde yönetilmesini gerektirmektedir. Bu nedenle, akıllı şebeke fikri, uygulamaları, yeni enerji kaynakları ihtiyacı gibi konular artarak önem kazanmaktadır. Bu çalışmada, asansör sisteminde kullanılan kata getirme sistemi ve asansörün çalışması sırasında ortaya çıkan rejeneratif enerjinin enerji ihtiyacının en yüksek olduğu saatlerde şebekeye aktarılması ile ilgili bir analiz yapılmıştır. İstanbul’da bulunan kurulu asansör sayısından yola çıkılarak, önerilen sistemde yapılan hesaplamalar ile 50 MW’lık bir güç karşılığı enerji tasarrufu elde edilebileceği öngörülmüştür

Dissociation of women from their selves: speech designated as sophrosyne

Since the ancient Greeks, sound production has been considered to be associated with the quality of voice and the use of voice under a general rubric of gender. Female voice has often been thought as an example of deviance from self-control; therefore, a pseudo need for putting a "door on the female mouth" has been constructed by the patriarchal culture. Masculinity in this culture defines itself by its different use of sound, namely the masculine virtue of sophrosyne or self-control. In this understanding, female virtue is coextensive with female obedience to male and the dissociation of women from their own emotions. Silence is seen to be the realm of women, which results in the construction of "othernesss" of women's language, since they are considered to lack the ability to control their speech. Under this condition, female words become some kind of lack of words and require to be channeled into rational discourse that belongs to men. In her essay "The Gender of Sound", Anne Carson examines how our presumptions about gender affect the way we hear sounds and raises the question if "there might not be another idea of human order than repression. Related to and as an extension of this question, it will be questioned if it may become possible to construct narrative in the feminine in this paper. For this purpose, it will be focused on Carson's "The Glass Essay" and the question if there is another human essence of self within the context of her views on this subject

Development and evaluation of ensemble learning models for detection of distributed denial-of-service attacks in ınternet of things

Internet of Things that process tremendous confidential data have difficulty performing traditional security algorithms, thus their security is at risk. The security tasks to be added to these devices should be able to operate without disturbing the smooth operation of the system so that the availability of the system will not be impaired. While various attack detection systems can detect attacks with high accuracy rates, it is often impossible to integrate them into Internet of Things devices. Therefore, in this work, the new Distributed Denial-of-Service (DDoS) detection models using feature selection and learning algorithms jointly are proposed to detect DDoS attacks, which are the most common type encountered by Internet of Things networks. Additionally, this study evaluates the memory consumption of single-based, bagging, and boosting algorithms on the client-side which has scarce resources. Not only the evaluation of memory consumption but also development of ensemble learning models refer to the novel part of this study. The data set consisting of 79 features in total created for the detection of DDoS attacks was minimized by selecting the two most significant features. Evaluation results confirm that the DDoS attack can be detected with high accuracy and less memory usage by the base models compared to complex learning methods such as bagging and boosting models. As a result, the findings demonstrate the feasibility of the base models, for the Internet of Things DDoS detection task, due to their application performance

Physician’s juristic role

This article discusses the normative and descriptive aspects of the physician’s juristic role and responsibilities according to Islamic law. In discussing the normative aspect of the physician’s juristic role in Islamic bioethics, one must first distinguish the juridical aspect of Islamic bioethics from bioethical views of Muslims. While the juridical aspect of Islamic bioethics is based upon the SharTah, the divine law revealed to the Prophet Muhammad, and the hermeneutic principles established to study and apply its norms and commands to concrete situations, bioethical views of Muslims may not necessarily be based upon this revelation. It is therefore possible for a Muslim physician to view the role of the physician based on bioethical opinions formulated by non-Muslims without referring to revelation

Değişen Dünyada Eğitimimiz: Olgular, Seçenekler

The study presents the educational outlooks of ‘developed’ and ‘developing’ cultures through a historical and comparative framework, showing with statistical data that educational problems are not the monopoly of developing nations. The fact that the so-called ‘developed’ societies also seem to violate the philosophies underlying universal documents of human rights is illustrated through data from those societies. Likewise, the Turkish educational system is presented through a historical framework; the reasons why compulsory education has been extended to eight years are stated. The paper emphasizes the point that a truly humane educational framework, respectful of human rights as stated in universal documents and focusing on the aim of education as “the means of the human being to search for his/her humanity ” cannot be imported from other cultures which are plagued with their own educational problems. The characteristics of such an education as perceived by the author are delineated.Çalışma, eğitimin genel olarak dünyadaki konum ve durumunu tarihsel bir çerçeve içinde kıyaslamak olarak ele almakta, eğitim sorunlarının yalnız, gelişmekte olan toplumlarda değil, gelişmiş olarak kabul edilen toplumlumlarda da, evrensel insan haklarını belirten bildirgeleri ihlal eder durumda olduğunu, verilerle göstermektedir. Ayrıca ülkemizde eğitime yine tarihsel bir çerçeve içinde bakılmış, bugünkü ilköğretimin sekiz, yıla uzatılması üzerinde durulmuş, insan haklarına saygılı, “insanın insanlığını aramasına yol gösteren" bir eğitimin başka ülkelerden ithal edilemeyeceği konusuna ağırlık verilerek, yazara göre böyle bir eğitimin özellikleri belirtilmiştir

Plant identification using local invariants: dense sift approach

In this thesis, we investigate the use of Dense SIFT approach in automatic identification of plants from photographs. We concentrate on owering plants and evaluate three alternative approaches. In the first one, we classify the plant directly using the dense SIFT method, using appropriate parameters that are found using experimental validation techniques. In the second approach, we first identify the dominant colour in the photograph and use a separate classifier in each of the colour cluster. The second approach is intended to reduce the problem complexity and the number of classes handled by each classifier. In this approach, the classifier for red owers will not know about a plant that does not ower in red; furthermore a plant that is only observed with red owers will only be handled by that classifier. In a third approach, we precede the second approach by adding a Region of Interest detector, in order to extract the flower color more reliably. We find that enhancement of Dense SIFT features based identification is possible with saturation-weighted hue histogram based color clustering and region of interest detector. Using the proposed system, we obtain a 0:60 accuracy on the ower subset in the LifecLEF 2014 database

Predicting mechanical properties in geopolymer mortars, including novel precursor combinations, through XGBoost method

Concrete is the most widely used material in the building industry due to its affordability, durability, and strength. However, considering carbon emissions, it is believed that concrete will be replaced by geopolymers in the future. As numerous parameters significantly affect the strength of geopolymers, the performance of potential algorithms for strength prediction needs to be evaluated for different binders to select an appropriate algorithm. This study employs machine learning approaches to provide the best prediction method for the flexural strength and compressive strength of geopolymers. A new dataset containing 533 compressive strength and 533 flexural strength values of geopolymers with different binders such as waste glass (GW), obsidian (OB), and fly ash was created. The best prediction solution, with R2 = 0.981 for compressive strength and R2 = 0.898 for flexural strength, was obtained from the extreme gradient boosting (XGBoost) algorithm. Additionally, several other machine learning models were employed, including linear regression, k-nearest neighbors, deep neural network, and random forest, with corresponding determination coefficient (R2) values of 0.763, 0.804, 0.93, and 0.96, respectively. These models were trained and evaluated using a dataset encompassing features such as binder types, age, and heat, to forecast the mechanical properties of geopolymers. Among these models, XGBoost demonstrated the highest R2 value, indicating superior performance in predicting both compressive and flexural strengths. The findings of this study provide valuable insights into the selection of appropriate machine learning algorithms for predicting mechanical properties in geopolymers, thus contributing to advancements in sustainable construction materials

Evaluation of Renewable Energy Alternatives for Turkey via Modified Fuzzy AHP

The importance of renewable energy is increasing both with the inadequacy of traditional energy resources and environmental awareness. Turkey has a large potential for renewable energy sources, and utilizing the potential is an inevitable choice for increasing its self-sufficiency with an environmentally friendly way. Therefore, evaluation of renewable energy alternatives for the country and determination of the most suitable renewable energy alternative are important issues to make reasonable energy investment plan.  In this study, we evaluate the renewable energy alternatives of Turkey using Modified Fuzzy Analytic Hierarchy Process. Renewable energy alternatives considered in the study are hydro, wind, solar, biomass and geothermal energy. Four main criteria and eight sub criteria are used to evaluate five renewable energy alternatives. The obtained results indicate that solar energy is the best alternative, and wind energy is the second best alternative for Turkey. The conclusion reached by this study is also support successful realization of the Vision 2023 energy targets. Keywords: Fuzzy Analytic Hierarchy Process, Renewable Energy, Energy Strategy. JEL Classification:  D81, Q20, Q38 DOI: https://doi.org/10.32479/ijeep.734