401 research outputs found
Qualitative and Artificial Intelligence-Based Sentiment Analyses of Anti-Lgbti Plus Hate Speech on Twitter in Turkey
No full textOBAN, Volkan/0000-0003-1046-9155; Dogan, Muzaffer Berna/0000-0003-0626-6582; Dikec, Gul/0000-0002-7593-4014The aim of this study was to evaluate hate speech in Turkish LGBTI+-related tweets during a one-month period of artificial intelligence-based sentiment analyses. Turkish tweets related to LGBTI+, were retrieved using Python library Tweepy and were evaluated by sentiment analysis. The researchers then performed a qualitative analysis of the most frequently liked and retweeted tweets (n = 556). Sentiment analysis revealed that 69.5% of tweets were negative, 23.3% were neutral, and 7.2% were positive. The qualitative analysis was grouped under seven themes: LGBTI+ Club; Terrorism and Terrorist Organization Membership; Perversion, Illness, Immorality; Presence in History; Religious References; Insults; and Humiliation. The results of this study show that anti-LGBTI+ hate speech in Turkey is significant in terms of both quality and quantity. As LGBTI+ individuals are at risk for excess mental distress and disorders, it is important to understand the risks and other factors that ameliorate stress and contribute to mental health in social media.Science Citation Index Expanded - Social Science Citation Inde
Kinstate intervention in ethnic conflicts : Albania and Turkey compared
No full textAlbania and Turkey did not act in overtly irredentist ways towards their ethnic brethren in neighboring states after the end of communism. Why, nonetheless, did Albania facilitate the increase of ethnic conflict in Kosovo and Macedonia, while Turkey did not, with respect to the Turks of Bulgaria? I argue that kin-states undergoing transition are more prone to intervene in external conflicts than states that are not, regardless of the salience of minority demands in the host-state. The transition weakens the institutions of the kin-state. Experiencing limited institutional constraints, self-seeking state officials create alliances with secessionist and autonomist movements across borders alongside their own ideological, clan-based and particularistic interests. Such alliances are often utilized to advance radical domestic agendas. Unlike in Albania's transition environment, in Turkey there were no emerging elites that could potentially form alliances and use external movements to legitimize their own domestic existence or claims
Word sense disambiguation using semantic kernels with class-based term values
No full textIn this study, we propose several semantic kernels for word sense disambiguation (WSD). Our approaches adapt the intuition that class-based term values help in resolving ambiguity of polysemous words in WSD. We evaluate our proposed approaches with experiments, utilizing various sizes of training sets of disambiguated corpora (SensEval(1)). With these experiments we try to answer the following questions: 1.) Do our semantic kernel formulations yield higher classification performance than traditional linear kernel?, 2.) Under which conditions a kernel design performs better than others?, 3.) Does the addition of class labels into standard term-document matrix improve the classification accuracy?, 4.) Is their combination superior to either type?, 5.) Is ensemble of these kernels perform better than the baseline?, 6.) What is the effect of training set size? Our experiments demonstrate that our kernel-based WSD algorithms can outperform baseline in terms of F-score
A novel semantic smoothing kernel for text classification with class-based weighting
No full textAltınel, Berna (Dogus Author), Diri, Banu (Dogus Author), Ganiz, Murat Can (Dogus Author) -- #articleinpress#Altınel, Berna (Dogus Author), Diri, Banu (Dogus Author), Ganiz, Murat Can (Dogus Author)In this study, we propose a novel methodology to build a semantic smoothing kernel to use with Support Vector Machines (SVM) for text classification. The suggested approach is based on two key concepts; class-based term weighting and changing the orthogonality of vector space. A class-based term weighting methodology is used for transformation of documents from the original space to the feature space. This class-based weighting basically groups terms based on their importance for each class and consequently smooths the representation of documents. This is accomplished by changing the orthogonality of the Vector Space Model (VSM) with introducing class-based dependencies between terms. As a result, on the extreme case, two documents can be seen as similar even if they do not share any terms but their terms are similarly weighted for a particular class. The resulting semantic kernel can directly make use of class information in extracting semantic information between terms, therefore it can be considered as a supervised kernel. For our experimental evaluation, we analyze the performance of the suggested kernel with a large number of experiments on benchmark textual datasets and present results with respect to varying experimental conditions. To the best of our knowledge, this is the first study to use class-based term weighting in order to build a supervised semantic kernel for SVM. We compare our results with kernels that are commonly used in SVM such as linear kernel, polynomial kernel, Radial Basis Function (RBF) kernel and with several corpus-based semantic kernels. According to our experimental results the proposed method favorably improves classification accuracy over linear kernel and several corpus-based semantic kernels in terms of both accuracy and speed
VIBRATIONAL SPECTRA OF THE MLCl COMPLEX FROM THEORETICAL CALCULATIONS
No full textAuthor Institution: Department of Physics, Mustafa Kemal University, Hatay, Turkey, 31034 (email to B.C.: [email protected])The geometric and vibrational parameters (harmonic and anharmonic frequencies) of the MLCl [M= Mn, Fe, Co, Ni, Cu, Zn, Cd, Hg; L= Ethylenediamine (en)] donor-acceptor complexes have been studied by using HF and MPW1PW91+iop(3/76=00572004280)/gen methods. Binding, reorganization, atomization, HOMO-LUMO and ionization potential energies have also been calculated with the same method. SQM calculations have been performed by using anharmonic frequencies and experimental data. The obtained results were found to be in good agreement with the corresponding experimental findings
Ocular findings in patients with psoriasis
No full textBackground Psoriasis is a chronic inflammatory disease affecting skin, nails, and joints. Although there are not many reports in the literature, ocular findings occur in approximately 10% of patients, in mostly those who have psoriatic arthritis. In this study, we aimed to evaluate eye involvement in psoriasis patients. Methods This study was performed on a total of 100 psoriasis patients and a group of 100 healthy individuals. History was taken from all study and control subjects, and dermatological, systemic, and ophthalmological examinations were performed and Schirmer and BUT values were measured. Constant variables were compared using the t-test, and categorical variables were compared using chi-square test. Relationship between ocular findings and sex, age, duration of psoriasis, PASI score, presence of psoriatic plaques on the eyelid, nail involvement, and psoriatic arthritis was evaluated using logistic regression analysis. Statistical analyses were performed individually for both right and left eyes. Results The number of ocular findings in both eyes in the patient group was found to be statistically higher than that in the control group. Schirmer and BUT values were statistically lower in the patient group than those in the control group. Conclusions Although results of our study support the necessity of routine ophthalmological examination of psoriasis patients for early diagnosis and treatment, we believe that further studies are required on the etiopathogenesis of ocular involvement in psoriasis patients
Novel hybrid treatments of textile wastewater by membrane oxidation reactor: Performance investigations, optimizations and efficiency comparisons
No full textFeasible reclamation of industrial wastewaters by consuming less resource and time requires researchers to develop advanced and sophisticated solutions to meet today's versatile needs. In this respect, novel technological applications of hybrid membrane oxidation reactor (MOR) comprising of the Fenton or photo-Fenton enhanced ultrafiltration (FEUF and pFEUF), was demonstrated for treating textile washing wastewater. Their comparative hybrid performances were explored based on response surface analyses of Taguchi experimental designs that were optimized for maximized responses at minimum oxidant and acid consumptions. From eleven specific variables, those affecting the hybrid treatment performances at significant levels were found as H2O2 amount, process time, membrane type, Fe2+ concentration and temperature. The pFEUF treatment showed better and faster organics removal efficiency than by FEUF, and the UF process was seen to be more affected from changing operational conditions in pFEUF. Organic pollutants were oxidized by 56.6 +/- 8.7% degradation and 31.5 +/- 3.2% mineralization, while UF allowed a synergistic contribution to the hybrid MOR performance by 38.1 +/- 4.7% and 17.3 +/- 3.1%, respectively. Compared to simultaneous MOR and external UF after Fenton, sequential MOR was found as the best solution by an efficiency of 84.5% COD, 70.5% TOC, and 155.6 L/m(2).h. The effluents could be readily produced with quality suitable for directly discharging to the sewage infrastructure system resulting in a complete treatment. This study proved that the developed MOR techniques are technologically favorable for the treatment of industrial organic wastewaters due to high treatment performances and less resource, time and land needs. It can be finally declared that they can be used as rather attractive solutions for not only wastewater reclamation but also water recovery by further handling of their effluents. (C) 2019 Elsevier B.V. All rights reserved
Recommended from our members
Essays on Food Security, Gender and Agriculture
No full textFood insecurity remains a major challenge worldwide with an uneven distribution towards developing countries. Persistent food insecurity is a cause of concern as lack of adequate consumption of food has long-term implications for both individuals and societies. As population growth, rising incomes, and rapid urbanization increase the pressure on agriculture via pressure on land and demand for food, food insecurity will remain a challenge requiring effective policy interventions in near future. This dissertation investigated the potential means through which food insecurity can be alleviated. In addition to a background chapter examining long term patterns of undernourishment and future threats to global food security, three empirical chapters examined the implications of foreign direct investment in agriculture for food security in the host country, how integration to markets affects the food security status of smallholder producers in Tanzania using data from Tanzania National Panel Survey 2014-15, and effect of women's empowerment on child nutrition based on data from Tanzania Demographic and Health Surveys (DHS) 2015. The findings of this dissertation show that mainstream policy approaches (i.e, increased FDI or more market oriented agriculture) do not always benefit the most vulnerable. Alleviating food insecurity requires a better understanding of complex social, economic and cultural factors and more inclusive policies. Transformation of food production systems and empowering the most vulnerable populations are inevitable to ensure global food security.Doctor of Philosophy (Ph.D.
In Silico Vorhersage der Auflösungsraten von Pharmazeutische Inhaltsstoffe: Micro- kinetisches Modell Basierend auf Spiral Auflösung
No full textIn this work, a computational protocol is proposed to predict the dissolution rates of molecular crystals that found usages in pharmaceutical industry to speed up the drug discovery processIn dieser Arbeit wird ein rechner-gestütztes Protokoll zur Vorhersage von Auflösungsraten molekularer Kristalle, welche in der Pharmaindustrie verwendet werden, vorgeschlage
Quasi-greedy bases for sequences with gaps
No full textIn this paper, we establish new results in the theory started by T. Oikhberg in Oikhberg (2018) where the author joins greedy approximation theory with the use of sequences with gaps. Concretely, we study and provide some answers to three open questions related to quasi-greedy bases for sequences with gaps posed in Oikhberg (2018)[Section 6].Fil: Berasategui, Miguel Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; ArgentinaFil: Berna Larrosa, Pablo Manuel. Universidad San Pablo; Españ
- …
