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A new a flow-based approach for enhancing botnet detection using convolutional neural network and long short-term memory
No full textDespite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. Due to the frequent adaptation of botnets to evolving responses offered by host-based and network-based detection mechanisms, traditional methods are found to lack adequate defense against botnet threats. In this regard, the suggestion is made to employ flow-based detection methods and conduct behavioral analysis of network traffic. To enhance the performance of these approaches, this paper proposes utilizing a hybrid deep learning method that combines convolutional neural network (CNN) and long short-term memory (LSTM) methods. CNN efficiently extracts spatial features from network traffic, such as patterns in flow characteristics, while LSTM captures temporal dependencies critical to detecting sequential patterns in botnet behaviors. Experimental results reveal the effectiveness of the proposed CNN-LSTM method in classifying botnet traffic. In comparison with the results obtained by the leading method on the identical dataset, the proposed approach showcased noteworthy enhancements, including a 0.61% increase in precision, a 0.03% augmentation in accuracy, a 0.42% enhancement in the recall, a 0.51% improvement in the F1-score, and a 0.10% reduction in the false-positive rate. Moreover, the utilization of the CNN-LSTM framework exhibited robust overall performance and notable expeditiousness in the realm of botnet traffic identification. Additionally, we conducted an evaluation concerning the impact of three widely recognized adversarial attacks on the Information Security Centre of Excellence dataset and the Information Security and Object Technology dataset. The findings underscored the proposed method's propensity for delivering a promising performance in the face of these adversarial challenges
A New Median Filter Circuit Design Based on Atomic Silicon Quantum-Dot for Digital Image Processing and IoT Applications
No full textDigital image processing (DIP) is the ability to manipulate digital photographs via algorithms for pattern detection, segmentation, enhancement, and noise reduction. In addition, the Internet of Things (IoT) acts as the eye and system for all DIP in various applications. It can possess a camera or another image sensor in order to capture real-time data from its environment. All vital data is processed by image processing in such a way that it recognizes the object, detects an anomaly, and automatically decides in real-time. In addition, in an IoT system, the median filter is the technique used for noise reduction by substituting the value of the pixel with the central value of the surrounding pixels. It provides speed and efficiency for quick analysis in all IoT systems. However, the images can get corrupted, especially in resource-constrained IoT devices with small cameras, because of random glitches. Moreover, using new quantum technology like atomic-scale silicon dangling bond (DB) logic circuits, which have advanced in fabrication and become a strong contender for field-coupled nano-computing, can solve previous problems in IoT systems. In this article, we propose a unique quantum CSM based on two new proposed Mux and De-mux. The proposed CSM can be used for computational circuits like median filter circuits (MFC) in a wide range of digital circuits, specifically IoT devices. The proposed design is verified and validated using the powerful SiQAD tool. When comparing CSM to the newest designs, the suggested quantum circuit uses 85% less energy and takes up 61% less area
Frontal lob tümörü olan bireylerde sosyal kognisyonun video temelli gerçek yaşam senaryosu ile değerlendirilmesi: pilot çalışma
Get PDFBu araştırmada frontal lob beyin tümörlü bireyler ve sağlıklı bireylerde sosyal kognisyon becerilerinin incelenmesi, kullanılan testler ile dilin pragmatik bileşenlerine ulaşılması amaçlanmıştır. Araştırmaya toplam 8 Frontal Lob Tümörü (BT) ve 8 sağlıklı kontrol olmak üzere 16 birey dahil edilmiştir. 16 katılımcıdan sosyodemografik bilgiler alındıktan sonra katılımcılara sırasıyla BT grubu için Addenbrook kognitif muayenesi ve kontrol grubuna Montreal Bilişsel Değerlendirme Ölçeği (MOCA) ve sonrasında her iki gruba da Video-temelli Sosyal Senaryo: Sosyal Kognisyonun değerlendirilmesi için geliştirilen pilot araç, M.D. Anderson Beyin Tümörü Semptom Envanteri (MDA-BTSET) uygulanmıştır. Ölçekler yüz yüze görüşme sağlanarak uygulanmıştır. Veriler ses kayıt cihazı ile kaydedilmiş, elde edilen anlatı örnekleri çevrim yazıya dönüştürülmüştür. Dönüştürülen çevrim yazı incelenerek kullanılan içsel durum terimleri manuel olarak sayılmıştır. Bu terimler kognitif, fizyolojik, emosyonel, linguistik ifadeler ve metafor olarak sınıflandırılabilir. Kontrol grubunun Emosyonel terim puanları, BT grubunun Emosyonel terim puanlarından anlamlı olarak daha yüksektir (Mann Whitney U test; U=11,5; Z=-2,171; p=0,030,05). Kontrol grubu ile BT grubu arasında Fizyolojik bakımından istatistiksel olarak anlamlı bir fark yoktur. (Mann Whitney U test; p>0,05) Kontrol grubu ile BT grubu arasında Kognitif ve Metafor bakımından istatistiksel olarak anlamlı bir fark yoktur (Independent samples t test; p>0,05). Elde edilen bulgular, BT hastalarının emosyonel ve linguistik terim kullanımlarının kontrol gruplarına göre daha düşük performans sergilediklerini göstermektedir. Bu sonuçlar, beyin tümörlerinin sosyal kognisyon ve dil üzerinde olumsuz etki yaratabileceğine işaret etmektedir. Tedavi veya tümörün kendisinden kaynaklanan sosyobilişsel işlevlerdeki bozuklukların, diğer insanların duygusal ve zihinsel bakış açılarını tanıma ve anlama gibi kişilerarası becerileri bozabileceği saptanmıştır. Ayrıca, beyin tümörü nedeniyle pragmatik dil becerilerinde yaşanan bozulmaların hastaların günlük yaşamı ve sosyal ilişkilerini olumsuz etkileyebilir. Beyin tümörü hastalığının ve tedavisinin, bireyler üzerinde sosyobilişsel fonksiyonları önemli ölçüde etkisinin olduğu sonucuna varılmıştır. Sonuç olarak BT hastalarında yalnızca nörokognitif değerlendirmelere değil, aynı zamanda sosyal biliş ve dil kullanımına odaklanan kapsamlı değerlendirme yöntemlerine de ihtiyaç vardır.The aim of this study is to examine social cognition skills in individuals with frontal lobe brain tumors (BT) and healthy individuals, and to access the pragmatic components of language through the tests used. A total of 16 individuals, including 8 with Frontal Lobe Tumor (BT) and 8 healthy controls, participated in the study. After collecting sociodemographic information from 16 participants, the Addenbrooke's Cognitive Examination was administered to the BT group, and The Montreal Cognitive Assessment (MOCA) was administered to the control group, respectively. Subsequently, both groups were evaluated using a pilot tool developed for assessing social cognition: the video-based social scenario. Finally, the M.D. Anderson Symptom Inventory - Brain Tumor (MDASI-BT) was administered to all participants. The control group's Emotional term scores were significantly higher than those of the BT group (Mann Whitney U test; U=11.5; Z=-2.171; p=0.030.05). There was no statistically significant difference between the control group and the BT group in terms of Physiological terms (Mann Whitney U test; p>0.05). Additionally, no statistically significant difference was found between the control group and the BT group in terms of Cognitive and Metaphorical expressions (Independent samples t-test; p>0.05). The findings indicate that BT patients perform worse in the use of emotional and linguistic terms compared to the control group. These results suggest that brain tumors may adversely affect social cognition and language. It was determined that disorders in sociocognitive functions, potentially arising from the treatment or the tumor itself, can impair interpersonal skills such as recognizing and understanding the emotional and mental perspectives of others. Moreover, the deterioration in pragmatic language skills due to brain tumors can negatively impact patients' daily lives and social relationships. It is concluded that the disease and treatment of brain tumor significantly influence sociocognitive functions in individuals. Consequently, there is a need not only for neurocognitive assessments in BT patients but also for comprehensive evaluation methods focusing on social cognition and language use
Transition from edge- to bulk-currents in the quantum Hall regime
Get PDFThe integer quantum Hall effect can be observed in a two-dimensional conductor penetrated by a perpendicular magnetic field and with edges connecting the current carrying contacts. Its signature is a state of quantized Hall and simultaneously vanishing longitudinal resistances. A widely accepted model is the Landauer-B & uuml;ttiker picture, which assumes an incompressible, i.e., electrically insulating bulk state surrounded by current carrying one-dimensional edge channels. This single-particle model is challenged by the screening theory. It derives that electron-electron interaction leads to a fragmentation of the Hall bar into compressible and incompressible strips, where the current flows inside the incompressible strips. Because the latter gradually shifts from the sample edges into the bulk as the magnetic field is increased, it suggests a transition from edge- to bulk-current. We present direct experimental proof of this transition. Our results support the screening theory
A New Progressive Motor-Control-Based Exercise Approach for Women with Diastasis Recti Abdominis: The Denizoglu Method
No full textPurposeThis randomized controlled study investigated the effectiveness of a novel progressive motor control-based exercise program (The Denizoglu Method) on IRD, abdominal endurance, pelvic floor dysfunctions, and body image satisfaction in women with diastasis recti abdominis (DRA).MethodsThis was a randomized controlled study of 50 women diagnosed with DRA within 1-3 years of the postpartum period. The progressive motor control-based exercise program and the conventional exercise program were performed 5 times a week for 8 weeks in a home-based and telerehabilitation setting. The primary outcome measured was inter-recti distance (IRD), while secondary outcomes included the static abdominal flexion endurance test, the Pelvic Floor Distress Inventory-20 (PFDI-20-20), and the Multidimensional Body-Self Relations Questionnaire (MBSRQ). All assessments were conducted both pre- and post-intervention.ResultsThe Denizoglu Method group demonstrated significant improvements in IRD, static abdominal flexion endurance, PFDI-20-20, and MBSRQ scores. Similarly, the conventional exercise training group exhibited statistically significant enhancements in IRD and PFDI-20-20 scores. However, the Denizoglu Method was found to be superior in improving IRD and abdominal endurance in women with DRA 1 to 3 years postpartum.ConclusionsThe Denizoglu Method emerges as a promising approach for managing DRA in clinical practice. It can be effectively implemented as a supervised home-based exercise program or integrated in women's health care centers during the 1 to 3 years postpartum period
Univariate Neural Network Quantitative (NNQ) Approximation by Symmetrized Operators
Get PDFThis paper deals not only with pointwise and uniform convergence but also Y-valued fractional approximation results by univariate symmetrized neural network (SNN) operators on Banach space Y,.. Moreover, our main motivation in this work is to compare the convergence results obtained by classical neural network (NN) operators and symmetric neural network (SNN) operators and try to convert them into numerical examples and graphs through computer programming language Python codes. As a result of this experimental study conducted under the regime of certain parameters, the convergence speed and results of SNN operators are superior to those of classical NN operators
7-11 yaş arası çocuklarda kekemelik yaygınlığının incelenmesi: Edirne örneklemi / Investigation of stuttering prevalence in children aged 7-11: Edirne sample
No full textBu çalışmanın amacı, 7-11 yaş arası çocuklarda Edirnedeki kekemelik yaygınlığının
incelenmesidir. Ayrıca bu durumu etkileyen çeşitli demografik, psikolojik ve çevresel
faktörlerin incelenmesi amaçlanmaktadır. Araştırma Edirne ilinde okul çağındaki çocuklar
üzerinde kesitsel araştırma yöntemi kullanılarak gerçekleştirilecektir. Bu kapsamda, kekemeliği
devam eden çocukların kendilerine, ailelerine ve kekemelik öyküleri ile ilişkili değişkenlerin
çocukların kekemelik durumuna etkileri incelenecektir.
Bu araştırmaya Edirne ilinden 7-11 yaş arası 418 çocuk katılım sağlamıştır. Bu çocuklardan
92’sinin kekemeliğinin geçtiği, 31’inin hala kekelediği ve ayrıca 43’ünün kız, 80’inin erkek
olduğu belirlenmiştir. İki aşamalı olarak hazırlanan araştırma sorularının ilk bölümünde;
kekemelik durumunun yanı sıra çocuğa ve ailesine ilişkin kişisel bilgiler yer almaktadır. İkinci
bölümde ise sadece kekemeliği devam eden ve kekemeliği geçen çocuklara yönelik olarak
hazırlanmış olan kekemelik durumunun başlangıcı, şiddeti, terapi alma durumu, kekemeliğin
getirmiş olduğu bedensel, psikolojik, sosyal ve duygusal sorunlar, kekemelik davranışları ile
kekemeliğe etki edecek pozitif ve negatif mizaç özellikleri incelenmiştir.
Araştırma bulguları, 7 yaş grubu ve 1.sınıfa giden çocuklardaki kekemelik yaygınlığının daha
fazla olduğunu göstermiştir. 26-35 yaş ile 36-45 yaş arası annelerin çocuklarındaki kekemelik
yaygınlığı ve 36-45 yaş arası babaların çocuklarındaki kekemelik yaygınlığı daha yüksek
bulunmuştur. Tek çocuk olan çocuklarda kekemelik görülme yaygınlığının daha fazla olduğu
belirlenmiştir. İlköğretim ve lise mezunu olan annelerin çocuklarında görülen ve İlköğretim
mezunu olan babaların çocuklarında görülen kekemelik yaygınlığı daha yüksek bulunmuştur.
Birinci ve ikinci derece akrabasında kekemelik geçmişi olan çocuklarda kekemelik
yaygınlığının daha fazla olduğu belirlenmiştir. Kekemeliği geçmiş olan çocukların gelir
düzeylerinin daha yüksek olduğu bulunmuştur. Kekemeliği devam eden çocukların başlangıç
yaşlarının 2-3 yaş arasında daha fazla olduğu görülmüştür. Kekemeliği devam eden çocukların
başlangıçtaki kekemelik şiddetlerinde çok hafif ve orta düzey olarak, kekemeliği geçmiş
çocuklarda ise hafif ve orta şiddetli kekemelik düzeylerinin fazla olduğu görülmüştür.
Kekemeliği devam eden çocukların okul başarılarında zorlandıkları görülmüştür. Kekemeliği
devam eden çocukların davranışlarında en fazla ses tekrarı, ses uzatma, blok, hece tekrarı ve
eklemeler yaşadığı görülmüştür. Kekemelik görülen çocuklarda en fazla (sıkılgan, duygusal,
çekingen) negatif mizaç özelliklerine, (meraklı, neşeli, düzenli) pozitif mizaç özelliklerine
sahip olduğu belirlenmiştir
Translation and validation of the Turkish version of the Subjective Index of Physical and Social Outcome (SIPSO)
No full textBackground & Objectives: Stroke is a disease that causes disability and death all over the world. Evaluation of physical and social outcomes after stroke is important in improving quality of life and well-being. The objective of this study is translating the Subjective Index of Physical and Social Outcome (SIPSO) into Turkish and examining its validity and reliability. Methods: This study used translation and back translation for the scale's language equivalence and expert opinion for the content validity. An expert panel and 8 individuals with SIPSO evaluated the scale for validity. The scale's reliability was assessed by internal consistency. Pearson correlation, and test-retest reliability were performed in 111 stroke patients. The scale's construct validity was tested with confirmatory factor analysis and exploratory factor analysis. Results: The Cronbach's alpha value was 0.972, and the scale was found to have a high degree of internal consistency. In confirmatory factor analysis, it was confirmed that the scale two factors: "physical and social outcomes". In the factor analysis, two factors emerged from the scale, and after the confirmatory factor analysis and scale modification, the fit indices of the model were found to provide a good level of validity. The scale is capable of distinguishing between introductory features and the physical and social consequences of stroke. Conclusion: SIPSO Turkish version is a valid and reliable scale that can be used in studies evaluating the physical and social effects of stroke
Neurodegenerative disorders: A Holistic study of the explainable artificial intelligence applications
No full textNeuro Degenerative Disorders (NDDs) involve progressive nerve cell loss, impacting functions like sensation, movement, memory, and cognition, posing life-threatening risks. Despite extensive research, viable therapies remain elusive due to complex pathophysiology. Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), shows promise in NDD diagnosis and treatment by leveraging vast datasets for accurate predictions. However, because AI models are "black boxes," explainable AI (XAI) had to be created to make sure that physicians and patients would trust and accept it. Early detection is critical to stop degeneration and make things better for patients. Many in-depth studies on XAI are designed explicitly for NDDs. Existing research does not constantly look at how to interpret NDDs, how to evaluate them, or how to keep them safe. This paper fills in these gaps by looking at and grouping XAI methods for different NDDs, to make them easier to understand and use in medical settings. In this paper, we look at the interpretability methods used in various NDD studies. The methods are split into five groups based on the conditions they are used to treat: Frontotemporal Dementia (FTD), Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), and Alzheimer's Disease (AD). It organizes XAI methods into groups and talks about their pros, cons, and clinical importance. The study also finds some important research gaps. For example, it says that there are no good security frameworks and that XAI is hard to use in real-life healthcare settings. By giving helpful information and a plan for future research, this paper shows how XAI could change how NDDs are found, treated, and predicted. AI technologies will be used more in healthcare, and this will help us learn more about these challenging conditions
Şizofreni tanısı almış bireylerin antropometrik ölçümleri ve biyokimyasal parametrelerinin değerlendirilmesi
Get PDFBu çalışmada, şizofreni tanısı almış bireylerde metabolik sağlık belirteçleri (açlık kan şekeri, lipid profili, beden kütle indeksi vb.) incelenmiş, bu belirteçlerin cinsiyet, eğitim seviyesi ve çalışma durumu gibi faktörlere bağlı farklılıkları değerlendirilmiştir. Çalışma, retrospektif, tanımlayıcı ve kesitsel bir araştırma olarak planlanmıştır. Araştırma, Niğde Ömer Halis Demir Üniversitesi Eğitim ve Araştırma Hastanesi Psikiyatri Bölümü'ndeki 2022 Eylül ile 2023 Eylül tarihleri arasında bilgileri kayıtlı olan 178 şizofreni hastasını kapsamaktadır. Veriler, hasta dosyalarından retrospektif olarak toplanmıştır. Hasta Bilgi Formu ile demografik ve klinik bilgiler; Antropometrik Ölçümler ile Bel Çevresi (BÇ), Beden Kütle İndeksi (BKİ), Biyokimyasal Parametreler Bilgi Formu ile Açlık Kan Şekeri (AKŞ), Düşük Yoğunluklu Lipoprotein Kolesterol (LDL-K), Yüksek Yoğunluklu Lipoprotein Kolesterol (HDL-K), Trigliserid (TG) gibi biyokimyasal değerler elde edilmiştir. Veriler, IBM SPSS 25.0 programında tanımlayıcı istatistikler, korelasyon analizleri ve Ki-Kare analizi ile değerlendirilmiştir. Araştırmada, kadınlarda BÇ ve BKİ değerlerinin erkeklere göre daha yüksek olduğu, erkeklerde ise lipid profili bozukluklarının daha belirgin olduğu saptanmıştır. AKŞ ortalaması 111.22 mg/dL olarak belirlenmiş ve diyabet riski açısından önemli bir faktör olduğu öngörülmüştür. Eğitim seviyesi düşük bireylerde metabolik sağlık risklerinin daha yüksek olduğu ve sağlıklı beslenme farkındalığının sınırlı olduğu görülmüştür. Çalışmayan bireylerde LDL-K ve TG seviyelerinin daha yüksek olduğu tespit edilmiştir. Metabolik sağlık profil bozukluğunun, antipsikotik ilaçların metabolik yan etkileri, sağlıksız beslenme ve sedanter yaşam tarzı ile ilişkili olduğu düşünülmektedir. Şizofreni tanısı almış bireylerde metabolik sağlık belirteçleri, cinsiyet, eğitim durumu ve çalışma durumu gibi faktörlere bağlı olarak farklılık göstermektedir. Bu bireylerin metabolik sağlık risklerinin azaltılması için bireyselleştirilmiş beslenme müdahaleleri, düzenli fiziksel aktivite ve farkındalık eğitimleri önerilmektedir.In this study, metabolic health indicators (e.g., fasting blood glucose, lipid profile, body mass index, etc.) in individuals diagnosed with schizophrenia were examined, and the variations in these indicators based on factors such as gender, education level, and employment status were evaluated. The study was designed as a retrospective, descriptive, and cross-sectional research. It included 178 schizophrenia patients whose records were available at the Psychiatry Department of Niğde Ömer Halis Demir University Training and Research Hospital between September 2022 and September 2023. Data were retrospectively collected from patient files. Demographic and clinical information was obtained through the Patient Information Form, anthropometric measurements included Waist Circumference (WC) and Body Mass Index (BMI), and biochemical data, such as Fasting Blood Glucose (FBG), Low-Density Lipoprotein Cholesterol (LDL-K), High-Density Lipoprotein Cholesterol (HDL-K), and Triglycerides (TG), were gathered using the Biochemical Parameters Information Form. The data were analyzed using IBM SPSS 25.0 software through descriptive statistics, correlation analyses, and Chi-square tests. The findings revealed that women had higher WC and BMI values compared to men, while men exhibited more pronounced lipid profile abnormalities. The mean FBG was determined to be 111.22 mg/dL, indicating a significant risk factor for diabetes. Individuals with lower education levels were found to have higher metabolic health risks and limited awareness of healthy eating. Unemployed individuals were observed to have elevated LDL-K and TG levels. Metabolic health profile abnormalities were associated with the metabolic side effects of antipsychotic medications, unhealthy dietary habits, and sedentary lifestyles.The study concluded that metabolic health indicators in individuals diagnosed with schizophrenia vary according to factors such as gender, education level, and employment status. To reduce metabolic health risks in this population, personalized nutritional interventions, regular physical activity, and awareness training are recommended