Fuzzy image segmentation using location and intensity information

The segmentation results of any clustering algorithm are very sensitive to the features used in the similarity measure and the object types, which reduce the generalization capability of the algorithm. The previously developed algorithm called image segmentation using fuzzy clustering incorporating spatial information (FCSI) merged the independently segmented results generated by fuzzy clustering-based on pixel intensity and pixel location. The main disadvantages of this algorithm are that a perceptually selected threshold does not consider any semantic information and also produces unpredictable segmentation results for objects (regions) covering the entire image. This paper directly addresses these issues by introducing a new algorithm called fuzzy image segmentation using location and intensity (FSLI) by modifying the original FCSI algorithm. It considers the topological feature namely, connectivity and the similarity based on pixel intensity and surface variation. Qualitative and quantitative results confirm the considerable improvements achieved using the FSLI algorithm compared with FCSI and the fuzzy c-means (FCM) algorithm for all three alternatives, namely clustering using only pixel intensity, pixel location and a combination of the two, for a range of sample of images

Smart driving : a new approach to meeting driver needs

The use of machine learning algorithms in different automated applications is increasing rapidly. The effectiveness of algorithms performances helps the user to operate their machine accurately and on time. Road sign classification is a very common type of problem for an automated driving support system. In this research, road speeding measure and sign identification is conducted using four popular machine learning algorithms to develop a smart driving system. This system informs forward-looking decision making and the initiation of suitable actions to prevent any future disastrous events. The robustness of the classification algorithms is examined for classification accuracy through 10-fold cross validation and confusion matrix. Experimental results proofs that the accuracy of Support Vector Machine (SVM) and Neural Network (NN) is almost 100 % and it is very promising compared to the earlier research performance. However, in terms of computational complexity NN is a slower classifier. Therefore, the experimental results suggest that SVM can make an effective interpretation and point out the ability of design of a new intelligent speed control system

Review on Fuzzy Clustering Algorithms

Image segmentation especially fuzzy-based segmentation techniques are widely used due to effective segmentation performance. For this reason, a number of algorithms are proposed in the literature. This paper presents a survey report of different types of classical fuzzy clustering techniques which are available in the literature

Fuzzy image segmentation considering surface characteristics and feature set selection strategy

The image segmentation performance of any clustering algorithm is sensitive to the features used and the types of object in an image, both of which compromise the overall generality of the algorithm. This paper proposes a novel fuzzy image segmentation considering surface characteristics and feature set selection strategy (FISFS) algorithm which addresses these issues. Features that are exploited when the initially segmented results from a clustering algorithm are subsequently merged include connectedness, object surface characteristics and the arbitrariness of the fuzzy c-means (FCM) algorithm for pixel location. A perceptual threshold is also integrated within the region merging strategy. Qualitative and quantitative results are presented, together with a full time-complexity analysis, to confirm the superior performance of FISFS compared with FCM, possibilistic c-means (PCM), and suppressed FCM (SFCM) clustering algorithms, for a wide range of disparate images

Experimental Study of Solar Collector Performance with Serpentine Mini-Channel

الهدف من هذه الدراسة تنفيذ التجريبية للتحقيق في الأداء الحراري للوح مجمع طاقة شمسية يعمل ع اساس قناة مصغرة. لتطبيق المبادلات الحرارية قناة صغيرة، فمن الضروري أن يكون أدوات تصميم مثالية لتنبأ انخفاض الضغط ونقل الحرارة. جميع التجارب العملية اجريت في مدينة بغداد خلال (تموز) عند زاوية ميلان (°30) درجة باتجاه الجنوب تحت ظروف الطقس المشمس. تم استخدام مائع عمل هو بروبلين كلايكول في جريان طباقي خلال تحقق التجارب العملية عند درجة حرارة دخول ثابتة (20) Cº-15)) ولمعدلات تدفق مختلفة (4.6 لتر/ساعة،5.77لتر/ساعة ،7.96لتر/ساعة ،11.2لتر/ساعة و18.35لتر/ساعة). تم تقييم اداء المجمع الشمسي من حيث معامل انتقال الحرارة، انخفاض الضغط، عامل الاحتكاك، طاقة الضخ، وفرق درجات حرارة الدخول والخروج. في هذه الدراسة تم اختبار الجهاز جود طلاء انتقائي وجود غطاء زجاجي بينت النتائج العملية ان زيادة معدل التدفق تؤدي الى زيادة معامل انتقال الحرارة بينما معامل الاحتكاك يقل. ايظا زيادة معدل التدفق تؤدي الى نقصان الفرق درجات الحرارة لمائع العمل بين الدخول والخروج.In this paper, experimental has been executed to investigate thermal performance of modified design of mini-channel plate solar collector. For the application of mini-channel heat exchangers, it is necessary to have perfect design tools for prophesy pressure drop and heat transfer. Experimental setup were carried out in Baghdad city from (July) with a tilt angle of (30º) to the south under sunny weather condition. The working fluid is propylene glycol in the laminar regime is used for experimental investigation at constant fluid inlet temperature (15 ºC - 20 ºC) and at different flow rates (4.6L/h, 5.77L/h, 7.96L/h, 11.2L/h, and 18.35L/h). The mini- channel solar collector performance is evaluated in terms of heat transfer coefficient, pressure drop, friction factor pumping power, and working fluid temperature difference between the outlet and the inlet .In this paper study the test rig with selective coating and with cover glass The experimental results show that an increase in mass flow rate the heat transfer coefficient is also increased while the friction factor is decreased. Also, increase in mass flow rate lead to the temperature difference between the outlet and the inlet working fluid decreases

Heat Transfer Analysis of Modified Solar Collector Plate with Mini-Channel

الهدف من هذه الدراسة تنفيذ التحليلات العملية والعددية للتحقيق في الأداء الحراري للوح مجمع طاقة شمسية يعمل على اساس قناة مصغرة. لتطبيق المبادلات الحرارية قناة صغيرة، فمن الضروري أن يكون أدوات تصميم مثالية لتنبأ انخفاض الضغط ونقل الحرارة. النموذج الرقمي يجمع بين الإشعاع الشمسي مع نقل الحرارة الحمل إلى لوحة امتصاص على أساس قناة صغيرة وكان عدد رينولد يتراوح بين 70 و 300 في معدل تدفق السوائل تراوحت من (4.6 لتر/ساعة الى 18.35 لتر/ساعة) يستخدم للتحقيق التجريبي في درجة حرارة مدخل السائل ( 20 درجة مئوية). كان السائل العامل البروبيلين جلايكول. يتم تقييم أداء قناة تجميع الطاقة الشمسية البسيطة من حيث معامل انتقال الحرارة، عدد نسلت، عامل الاحتكاك وضخ الطاقة. وتكشف النتيجة أنه عندما يكون هناك زيادة في معدل تدفق الكتلة من السائل المتدفق، فإن معامل انتقال الحرارة الحراري يزداد أيضا في حين ينخفض ​​معامل الاحتكاك.In this paper, experimental and numerical analyses have been executed to investigate the thermal performance of modified design of mini-channel plate solar collector. For the application of mini-channel heat exchangers, it is necessary to have perfect design tools for predicting the pressure drop and heat transfer. A numerical model combining solar radiation with convective heat transfer to the absorber plate based on mini-channel has been developed. Reynolds number ranged from 70 to 300 at the fluid flow rate ranged from 4.6 L/h to 18.35 L/h is used for experimental investigation at fluid inlet temperature (20°C); the working fluid is propylene glycol. The mini channel solar collector performance is evaluated in terms of heat transfer coefficient, Nusselt number, friction factor, and pumping power. The result revealed that when there is an increase in the mass flow rate of flowing fluid, the convective heat transfer coefficient is increased, while the friction factor is decreased

Calculating the Theoretical Octane Number for a Number of Petroleum Derivatives Using Quantum Mechanical Methods AM1 and PM3

This research included calculating a number of physical variables that affect the octane number using semi-empirical methods of quantum mechanics, including AM1, PM3, hardness (η), electron-chemical potential (µ), spherical electrophilic index (W, ∆G, ∆H, ∆S, ∆E and dipole moment). Multiple statistical analyses were used to find the relationship between the calculated variables and the practical value of the octane number and then calculate the octane number theoretically. Through the four-way statistical analysis, we obtained the best correlation coefficient (R2) for the variables (HOMO + η + ∆S + ∆E) calculated by the PM3 method (R2 = 0.998) and the correlation coefficient values for the variables (HOMO + η + W+ µ) calculated by the AM1 method (R2 = 0.980). Through the single and multiple statistical analysis, the most influential variables on the octane number values are (HOMO, LOMO)

Rheumatoid Arthritis Diagnosis Based on Intelligent System

التهاب المفاصل الروماتويدي  يؤثر على كثير من الناس مستهدفا المفاصل وخاصة المفاصل الصغيرة، ويستهدف جميع الأعمار حيث هو أكثر شيوعا في النساء. هذا المرض له العديد من الأعراض مشابهة لأمراض أخرى. لذلك، فمن الصعب جدا كشفه. كما أن أدوات التشخيص معقدة وغير اقتصادية. في هذا البحث، شبكة الذكاء الاصطناعي استخدمت لتشخيص والكشف المبكر عن التهاب المفاصل الروماتويدي وفقا للمعايير التي وضعتها الكلية الأمريكية للروماتيزم. أفضل أداء يحدث مع الحد الأدنى لعدد الخلايا العصبية المطلوبة عندما يكون عدد الخلايا العصبية هو 6. بحيث، فإن الأداء يساوي 10-10×3.8968. عند تقليل عدد الخلايا العصبية إلى 5 أو زيادة إلى 8، والنتيجة هي 0.0041 و  10-10×1.0611 ,على التوالي. مع ذلك، يمكن اعتبار جميع النتائج مقبولة و أن أفضل خيار لهذه التصاميم سيكون 6 خلايا عصبية من جانب التعقيد والدقة.The Rheumatoid Arthritis (RA) affects many people targeting their joints, especially small joints, and it targets all ages which it is more common in women. This disease has many symptoms similar to other diseases. Therefore, it is very hard to detect. Also, the diagnostic tools are complex and uneconomical. In this paper, artificial intelligence network used for diagnosis and early detection of RA in accordance with criteria developed by the American College of Rheumatology. The best performance occurs with the minimum number of neurons required when the number of neurons is 6. So that, the performance is equal to 3.8968x1010-.  When reducing the number of neurons to 5 or increasing to 8, the result is  0.0041 and 1.0611×10-10, respectively. However, all results can be consider acceptable and indicate that the best choice from this structure will be 6 neurons in the form of complexity and accuracy

Performance assessment of antenna array for an unmanned air vehicle

In this paper, the performance of Linear Antenna Array Element (LAAE) has been evaluated at the Base Station (BS) with a different number of elements for Unmanned Air Vehicle UAV application. The Switched Beam (SB) and Phase Array (PA) have been used as a steering beam mechanism. The beam steering tracker is based on the GPS points of the UAV and the BS. In addition, the Misalignment angle has been analyzed for SB and PA corresponding to the maximum speed of the UAV. The compression between SB and PA in term of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) and BER vs. Misalignment angle have been examined by using Matlab. The results show that the PA has better performance than SB in both terms under Additive White Gaussian Noise (AWGN) channel with an interference signal. When the number of the elements is eight provides longer distance than four by the factor (1.5 in SB case and 2 in PA case) and wider Misalignment angle range than twelve by factor (2 in SW case and 3 in PA case). Therefore, it is becoming a useful option for many applications

Needle stick injuries and their safety measures among nurses in Erbil Hospitals

Background: Needle stick injuries are serious professional hazards in the transfer of certain types of blood borne diseases such as hepatitis B virus, hepatitis C virus, and human immunodeficiency virus among healthcare workers. Objective: Firstly, to determine the prevalence and factors related to needle stick injuries. Secondly, to assess related safety measures among nurses in Erbil hospitals. Patients and Methods: A hospital based cross sectional study including a sample of 452 nurses. A representative supple sample size was calculated by using Epi info version 7.The sample was proportional to the population of nurses in each hospital. A convenient sampling technique was adopted in selection of studied sample from different teaching hospitals in Erbil city. Data were collected by using self-administered questionnaire, which included socio-demographic characteristics of participants and questions regarding needle stick injuries and preventive measures. (SPSS, Chicago, IL, USA), version 26) was applied for data entry and analysis. P value of ≤ 0.05 was considered as statistically significant. Results: Out of a total (452) study population, 56.9% were females and 43.1% were males. The mean ± SD of age was 36.2 ± 5.41, ranging from 21 to 54 year. The prevalence of needle stick injuries was 87.4% among nurses, and the widespread activity leading to NSIs was recapping of needles (81%). The average of non-reporting to supervisor of infection control was 77.2%.  The majority of NSIs took place in the morning (70.5%). There was a statistically significant association between NSIs and use of PPE, secure disposal of needle in the safety box, and use of auto-disable syringe during injection, in which NSIs were highest among those who not use or sometimes use the above mentioned safety measures, (P<0.001, P=0.002, and P=0.003 in respectively). Conclusion:This study showed that transverse needle stick injuries among nurses are very high and pose a rise in hazards for professional exposure to diseases transmitted by blood. The majority of nurses are not reporting the needle stick injuries to the supervisor of the infection control unit