Background: Acute cholecystitis is common surgical
problem, which was treated previously by conservative
treatment .Later early open has been introduced as an
alternative to interval for treatment of acute cholecystitis.
Early open was found to be a safe, successful with
comparable postoperative complication rate. With the
advent of laparoscopy laparoscopic have been used for
chronic cholecystitis and became the first line of
treatment. New reports have shown that laparoscopic can
be used as an alternative to open for surgical treatment of
acute cholecystitis.
Objectives: to compare the success, safety of early
laparoscopic versus early open as a primary treatment of
acute cholecystitis.
Methods: out of 68 patients were treated for clinical
acute cholecystitis between January 2002 and February
2004 in the department of surgery, at Al – Kindy teaching
hospital. A total of 62 patients underwent early for acute
cholecystitis as soon as possible after diagnosis. The
preferred preoperative imaging technique was ultrasound.
30 (48.3%) of the operations were attempted
laparoscopically, whereas the remaining 32 patients
(51.7%) underwent initial open .
Results: The mean operative time for the open cases
was 75 minutes versus 60 minutes for the laparoscopic
group. There was no perioperative mortality in either
group. The incidence of conversion to open was 10% (3
patients). Surgical complications related to laparoscopic
and open occurred in 2 (6.6%) and 3 (9.3%) cases,
respectively. There was no difference between the open
and laparoscopic groups in regard to the major
postoperative complications.
Conclusion: The current study shows that early
(whether performed by open or laparoscopically) is a
safe and effective treatment for acute cholecystitis. Low
conversion rates can be maintained with strict guidelines
for appropriate patient selection, adequate experience,
and proper laparoscopic technique.
In this work , a hybrid scheme tor Arabic speech for the recognition
of the speaker verification is presented . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural network has been used as a recognizer tor speaker verification after extract spectral features from an acoustic signal by Fast Fourier Transformation Algorithm(FFT) .
The system was im plemented using a PENTIUM processor , I000
MHZ compatible and MS-dos 6.2 .
The present calculation covers the building shield during irradiation process and under water storage of three milion curries Cobalt-60 radiation source the calculation results in design requirement of 8m depth of water in the source stoeage pool
This work presents plants recognition system with rotation invariant based on plant leaf. Wavelet energy features are extracted for sub-images (blocks) beside three of leaf shape features: [area, perimeter, circularity ratio]. (8) species of leaves are used in different size and color, (15) samples for each leaf are used. Leaves images are rotated at angles: 90˚, 180˚, 270˚(counterclockwise,clockwise). Euclidean distance is used, the recognition rate was 98.2% with/without rotation.
The conception and experimental assessment of a removable friction-based shear connector (FBSC) for precast steel-concrete composite bridges is presented. The FBSC uses pre-tensioned high-strength steel bolts that pass through countersunk holes drilled on the top flange of the steel beam. Pre-tensioning of the bolts provides the FBSC with significant frictional resistance that essentially prevents relative slip displacement of the concrete slab with respect to the steel beam under service loading. The countersunk holes are grouted to prevent sudden slip of the FBSC when friction resistance is exceeded. Moreover, the FBSC promotes accelerated bridge construction by fully exploiting prefabrication, does not raise issues relevant to precast co
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The current research dealt with the rapid development of industrial product design in recent times, and this development in the field of design led to the emergence of modern trends in many terms and theories to direct greater interest in the cognitive foundations of design and its relationship with the components of other natural sciences, and despite the impressive technological development, nature remains With its content of formative values and structural dimensions, it is the first source of inspiration and the source of all modern mathematical sciences and theories, as God made them tend towards organization to continue to provide us with endless inspiration. Hence, the fractional one, which is an important part of dedicating the d
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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Investment Bases directly and closely to an environment characterized by political, social and economic stability, and through a range of policies and institutions and economic laws that affect investor confidence and convince him directing investments to country without the other, where inter conditions and circumstances affecting the trends of capital and settle in, and political situation of the country and what is characterized of stability or disorder as well as economic conditions that are affected by what is distinguishes the country from geographic and demographic characteristics are reflected on availability of production elements and country's infrastructure.
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