Portal of Cihan University-Erbil Scientific Journals
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physiochemical and Sensory Properties of Pumpkin and Strawberry Jams Fortified with Chia Seed ( Salvia Hispanica L)
No full textSupplementation of jams with functional ingredients is one of the methods to develop healthier jams. The aim of this research was therefore to develop functional jams supplemented with chia seed (CS). Five formulations of two types of jams were selected (pumpkin (PJ) and strawberry jams (SJ) ) with different levels ( 0, 1.5, 3, 4.5 and 6% ) of CS was added. The jams were assessed chemically, sensorial and nutritionally a using ICP-OES. The results showed that the introduction of CS into PJ significantly increased protein, ash, cellulose content from 0.35%, 0.55 and 46.43 of control to 0.77%, 1.01 and 54.18 of sample containing 6% CS respectively. However pH, acidity and moisture decreased. Similarly protein, ash , cellulose of SJ jam increased from 0.44%, 0.58 and 14.55 of control sample to 0.93%, 0.93 and 16.75 of sample containing 6% CS respectively. Unlike PJ pH, and moisture increased with addition of CS. Antioxidant and total phenol content were not noticeably changed. The sensory data discovered that the addition of CS adversely affected all sensory attributes parallel with CS addition both jams, but appearance color and taste were more influenced particularly in PJ. The addition of CS in PJ increased the content of calcium, iron and zinc from <0.05 mg/kg (control) to 1121, 6.74 and 2.36 respectively. . In conclusion, the data of this study showed the PJ and SJ can be produced by the addition of as high as 6% CS with improved nutritional value and acceptable sensorial properties
Evaluation of ChatGPT’s Configuration Support for Network Connectivity and Security
No full textChatGPT is the world most famous AI interface operates by analyzing the prompt input text and generating coherent responses that predicts effectively your query by utilizing the knowledge it has acquired from its training data. Although this process may appear straightforward and authentic, it may give misleading results for more deep analysis specially for the network engineers. In this paper, evaluation of ChatGPT’s configuration support for network connectivity and security will be analyzed, by applying the commands generated by the ChatGPT AI to configure and secure an enterprise network designed with simulated cisco hardware, and analyzing the full network connectivity and security to determine if the ChatGPT AI prediction was accurately sufficient to run a full networ
Epidemiological Insights into TORCH Infections in the Population of Erbil City
No full textA seroepidemiological study of the TORCH panel was conducted on inhabitants of Erbil City to provide updated baseline data on TORCH prevalence. 508 individuals were included in this study. 218 (42.91%) were females and 290 (57.09%) were males. Their ages ranged from 13 to 63 year, the majority being within the age group (21-30 years), 162 (31.89%), (P < 0.05). 20 individuals (3.94%) tested positive for anti-TOX IgG antibodies. One of the 20 (5%) tested positive for anti-TOX IgM antibodies, who was a 32-year-old female. 128 individuals (25.2%) (all females) tested positive for anti-Rubella IgG antibodies. 40 individuals (7.87%) were positive for anti-CMV IgG antibodies. One of the 40 (2.5%) also tested positive for anti-CMV IgM antibodies, who was a 26-year-old male. 18 individuals (3.54%) tested positive for anti-HSV-1 IgG antibodies. One of the 18 (5.56%) also tested positive for anti-HSV-1 IgM antibodies. One 18-year-old male (0.2%) tested positive for anti-HSV-2 IgG antibodies, and none were positive for anti-HSV-2 IgM antibodies. The results suggest the presence of Toxoplasma, CMV, HSV-1 and HSV-2 infections among the community, the majority (P < 0.05) being CMV followed by TOX and HSV-1 and finally HSV-2. The positive IgG results of Rubella are most probably due to the obligatory vaccination program for females. Despite the fact that the majority of positive cases were for IgG, enhancing vaccination efforts and providing comprehensive health education is crucial for enhancing the well-being of the Erbil population
Strategy for Applying Artificial Intelligence in State Institutions
No full textبات الذكاء الاصطناعي وتطبيقاته العملية من اكثر المواضيع التي اخذت مجالا واسعا في الدراسات الحديثة واتسع نطاق دراسته ليشمل ميادين لم تكن معروفة منذ عقد مضى ، خاصة بعد ان دخلت تطبيقاته العملية مختلف نواحي الدولة من خطط واليات عسكرية واتمته متقدمة للنظام الاقتصادي وتطبيقات التجارة الدولية ودخول الذكاء الاصطناعي في تحسين وتقييم الاداء المؤسسي في الدولة ، وفقا لذلك ياتي البحث كمحاولة للوقوف على استراتيجية تطبيق الذكاء الاصطناعي في المؤسسات الحكومية وصولا الى عملية تقييم اداء مؤسسي يقوم على الحياد والموضوعية. يتكون البحث من مبحثين اساسيين بالاضافة الى المقدمة والاستنتاجات والتوصيات يتناول المبحث الاول المنطلقات الاساسية في استخدام الذكاء الاصطناعي من خلال ثلاث فقرات تتعلق الاولى بتعريف الذكاء الاصطناعي واستخداماته الحكومية وتختص الثانية بالتعرف على خصائص تطبيق الذكاء الاصطناعي في المؤسسات الحكومية في حين تتناول الثالثة تحديات تطبيق الذكاء الاصطناعي في مؤسسات الدولة ، اما المبحث الثاني فيدرس الخطة الاستراتيجية لتطبيق مخرجات الذكاء الاصطناعي في مؤسسات الدولة من خلال ثلاث فقرات ايضا اذ تدرس الفقرة الاولى استراتيجية اعادة البرمجة الهيكلية لمؤسسات الدولة اما الثانية فتتناول مزايا استخدام الذكاء الاصطناعي في مؤسسات الدولة في حين تتعلق الثالثة دور الذكاء الاصطناعي في تقييم الاداء المؤسسي .Artificial intelligence and its practical applications have become one of the topics that have taken up a wide scope in modern studies, and the scope of its study has expanded to include fields that were not known a decade ago, especially after its practical applications entered various aspects of the country, from military plans and mechanisms, advanced automation of the economic system, international trade applications, and the introduction of artificial intelligence. In improving and evaluating institutional performance in the country, accordingly, the research comes as an attempt to determine the strategy for applying artificial intelligence in government institutions to reach an institutional performance evaluation process based on impartiality and objectivity
Optimizing Health Pattern Recognition Particle Swarm Optimization Approach for Enhanced Neural Network Performance
No full textHealth pattern recognition is vital for advancing personalized healthcare interventions. This research introduces a synergistic approach, combining Fuzzy C-Means clustering with Particle Swarm Optimization (PSO), to optimize the hyperparameters of an Artificial Neural Network (ANN) and enhance health pattern recognition. Leveraging key features such as 'Smoker,' 'BMI,' and 'GenHlth,' Fuzzy C-Means reveals distinctive health clusters, providing nuanced insights into diverse health profiles within the dataset. Subsequently, the PSO algorithm systematically optimizes critical ANN hyperparameters, significantly decreasing the training loss to 0.004. This reduction underscores the effectiveness of the optimization process, indicating improved learning and predictive capabilities of the ANN. The proposed methodology not only refines health pattern recognition but also holds promise for personalized healthcare analytics. The identified clusters offer actionable insights for tailored interventions, addressing specific health profiles within the population. This research contributes to the evolving landscape of healthcare analytics by integrating advanced clustering and optimization techniques, paving the way for more effective and individualized healthcare strategies
The Effect of Probe Thinking Strategy (Application of Principles) on Acquisition of Some Basic Offensive Skills in Handball
No full textProbe thinking is the structure that emerges from the interaction between the student and what he encounters, rather than what he is taught, and thinking that is focused on posing questions and coming up with solutions, the spark that keeps a learner interested. Therefore, the present study was an attempt to investigate the possible effect of probe thinking strategy on acquisition of some basic offensive skills in handball. A control group and an experimental group were utilized in a pre-post-test design. Following the pre-test, the experimental group received the treatment whereas the control group did not. For the analysis, 20 learners from Cihan University-Erbil, Iraq, were taken into consideration. Descriptive and inferential statistics were used in the statistical analysis (i.e., Independent samples t-test) in terms of how the two groups performed on the pre- and post-tests. The results revealed that the use of probe questions strategy is effective for the Sports Sciences students to get better results regarding pass-test, dribble-test, and shot-test. The findings of the present study can benefit all the educators and the students as well to have a better performance in practical courses. At the same time, these results can be double checked for the other sports so that they can be generalized to all the branches of Sports Sciences
Intelligent Handwritten Identification Using Novel Hybrid Convolutional Neural Networks – Long-short-term Memory Architecture
No full textHandwritten character identification finds broad applications in document analysis, digital forensics, and human-computer interaction. Conventional methods encounter challenges in accurately deciphering a range of handwriting styles and variations. Consequently, investigating intelligent system for handwriting identification becomes crucial to enhance accuracy and efficiency. This paper introduces an innovative hybrid deep learning architecture, seamlessly integrating the strengths of convolutional neural networks (CNN) and long-short term memory (LSTM) within a one single framework. The combination of these structures enables the model to effectively capture both spatial features and temporal dependencies inherent in handwritten strokes, resulting in improved recognition performance. The proposed 2DCNN-LSTM algorithm has been tested on MNIST dataset. The proposed hybrid CNN-LSTM structure has been compared to conventional intelligent machine learning methods, and the results demonstrate the superior performance of the hybrid CNN-LSTM, showcasing heightened accuracy, sensitivity, specificity, and other evaluation metrics
Adverse Effects of Excessive Use of Some Beverages on Male Albino Rats
No full textBeverages are non-alcoholic drinks designed to induce stimulation by the addition of active compounds, particularly high levels of caffeine. They are currently promoted as agents that boost energy (both mental and physical capabilities), This study aims to assess the side effects of energy drinks, such as Red Bull and Red Strong, on numerous physiological parameters and histological characteristics of the liver and kidney in male albino rats. Fifteen rats were allotted into three groups: group (1) consumed distilled water as the control group, group (2) drank Red Strong energy, and group (3) drank Red Bull energy, administered orally by gavage once a day for 8 weeks, with each group receiving 2.0 mL/100 g of body weight in the energy drink. The outcome shows that the body weight gain increased significantly induced in high long-term energy drinking groups and elevated the liver function enzymes, including alanine transaminase, aspartate transaminase, total serum bilirubin, and alkaline phosphatase. Furthermore, it adversely affects renal function through increased urea, creatinine, uric acid, and decreased glomerular filtration rates. Furthermore, adverse influences on reproduction organs by a decline in testosterone and sperm properties. Histological studies showed alteration structure in energy-drinking groups such as degenerative kidney tubules, hemorrhage, shrinkage of the glomerulus and the dilated sinusoid, degenerative hepatocyte, and inflammation in the liver. The presented study showed that the high consumption of beverages (Red Strong and Red Bull) have adverse effects on the liver and kidneys of male albino rats
Comprehensive Evaluation and Management of Liver Hydatid Cyst.
No full textHydatid cyst infection is a severe disorder caused by exposure to the infectious form of the Echinococcus granulosus parasite, which is widespread worldwide. This study examined a total of 125 patients who were diagnosed with hepatic hydatid cysts based on clinical and surgical evaluations. Patients with cysts larger than 5 cm displayed markedly elevated levels of ALT, AST, and ALP in comparison to those with smaller cysts. The heightened levels suggest a disturbance in liver functionality resulting from the infection. Furthermore, the patients exhibited elevated serum bilirubin levels. An evident differentiation was observed between patients with cysts over 5 cm in size and those with smaller cysts, indicating have a higher effect on liver function in individuals with bigger cysts. A total of 225 hepatic hydatid cysts were diagnosed using CT scans. The predominant cyst phases seen were Stage I and II, accounting for 58% and 45% of cases, respectively. Upon diagnosis, 79% The cysts range in size from 5 to 10 cm. CT imaging provides additional features that aid in the identification of type I unilocular echinococcosis. However, it is important to note that no single imaging feature is clearly diagnostic of this type of cyst.. Nevertheless, imaging techniques can assist in differentiating these cysts from non-parasitic liver cysts. On the other hand, Type II, III, and V hydatid cysts can be accurately identified by their distinct imaging characteristics
The Role of Artificial Intelligence Application in Strategic Marketing Decision-Making Process
No full textThis review article examines artificial intelligence (AI)’s role in strategic marketing decision-making. The researchers interviewed experts with experience in decision-making and used Carrefour Iraq as a case study to identify themes on how humans use AI for better strategic marketing decision-making. The key themes in this review were factors such as big data, efficiency, quality, trust and limitations for prediction. The study has also looked into the marketing aspect of these themes within the scope of this research. The findings indicate that AI is recognized as a tool that may support humans in making strategic decisions in marketing. However, AI can technically make such decisions without human intervention; people do not want to give AI complete autonomy in decision-making. Furthermore, the result implies that rather than making decisions independently, AI is more frequently applied to enhance strategic decision-making. It suggests that Al aims to improve decision making-making rather than supplant people in daily life. In addition, the study makes the case that Al can assist humans in making better decisions by forecasting future scenarios that consider a particular action consequence