Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reduction in EEG complexity and decrease in EEG connectivity were investigated. Support vector machine and linear discriminate analysis methods were used to find the best combination of the EEG biomarkers to detect AD with significant performance. A total of 325,567 EEG biomarkers were investigated, and a panel of six biomarkers was identified and used to create a diagnostic model with high performance (≥85% for sensitivity and 100% for specificity).
Vol. 6, Issue 1 (2025)
This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreThe research aims mainly to the role of the statement style costs on the basis of activity based on performance (PFABC) to reduce production cost and improve the competitive advantage of economic units and industrial under the modern business environment dominated by a lot of developments and changes rapidly, which necessitates taking them and criticize them to ensure survival and continuity. The research problem is the inability of traditional cost methods of providing useful information to the departments of units to take many administrative decisions, particularly decisions related to the product and calculating the costs of the quality of the sound and the availability of the need and the ability to replace methods capa
... Show MoreObjective(s): The study aims to evaluating the quality of nursing care provided to children under five years to compare between quality related to type of health sectors; to determine the quality of nursing care and to compare between such care in Baquba Health Care Sector I and II.
Methodology: A descriptive study is carried out for the period from December 15th 2019 to May 1st 2020. A purposive "non- probability" sample, of (60) staff nurse and (60) children is selected. An adopted questionnaire has been selected for the study which consists of three parts. The first part is nurses’ socio-demographic characteristic; the second part is ch
... Show MoreThe study aimed to evaluate the benefits of transferrin saturation percentage (TSAT) and serum ferritin in assessing body iron status, which can influence erythropoietin treatment in patients with ESRD. Forty end-stage renal disease patients on regular hemodialysis participated in this study. Clinical data were obtained. Serum iron, total iron binding capacity, transferrin saturation, ferritin, albumin, creatinine, and C-reactive protein were investigated. Thirty healthy people were enrolled as a control group. ESRD patients had a mean age of 45.1±13.9 years, with 60% being males. They exhibited significantly lower hematocrit (25.3±6.5%), and higher platelet (285.7±148.1x10^9/L) and WBC (9.4±3.1x10^9/L) counts compared to healthy contro
... Show Moreالخلاصة: الحكة اليوريمية لدى مرضى غسيل الكلى يؤثر على أكثر من 40٪ من المرضى. وربما ترتبط الحكة المستمرة بمستويات عالية من الإنترلوكين 31. الاهداف: النظر إلى مستويات مصل إنترلوكين 31 لدى مرضى غسيل الكلى المصابين بمرض الكلى في المرحلة النهائية، سواء مع أو بدون حكة يوريمية. النتائج: لم يكن مستوى المصل [الوسيط (] لـ IL-31 في المرضى الذين يعانون من الحكة اليوريميةأو بدون حكة في عينة مصل ما قبل غسيل الكلى مختلفًا بشكل م
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