93,062 research outputs found
Automatic domain ontology extraction for context-sensitive opinion mining
Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline
Extruder for food product (otak–otak) with heater and roll cutter
Food extrusion is a form of extrusion used in food industries. It is a process by which a set of mixed ingredients are forced through an opening in a perforated plate or die with a design specific to the food, and is then cut to a specified size by blades [1]. Summary of the invention principal objects of the present invention are to provide a machine capable of continuously producing food products having an’ extruded filler material of meat or similarity and an extruded outer covering of a moldable food product, such as otak-otak, that completely envelopes the filler material
Parametric optimization of the femoropopliteal artery stent design based on numerical analysis
High-failure rates of Peripheral Arterial Disease (PAD) stenting were reported due to
the inability of certain stent strut configuration to accommodate severe biomechanical
environment of the Femoro-Popliteal Artery (FPA) such as bends, twists, and axially
compresses during limb flexion. The unique of mechanical deformation environment
in FPA has been considered one of main factors affecting the durability of the FPA
stent and reducing the stent life. Consequently, various optimization techniques have
been developed to improve the mechanical performance of the FPA stent. The present
work shown that, the first-two of twelve FPA resemble stent models stent models have
been selected with a net score of 3.65 Model I and, with a net score of 3.55 Model II
via applying Pictorial Selection Method. Finite Element Method (FEM) of
optimization study based-parameterization has been conducted for stent strut
dimensions, stents were compared in terms of force-stress behavior. Multi Criteria
Decision Making (MCDM) method has been utilized to identify the best combination
of strut dimensions. The strut thickness parameterization results were in relation T α
1/σ (T is strut thickness) for both models with all mechanical loading modes.
Moreover, the strut width parameterization results were in relation W α 1/σ (W is strut
width) for both models with all mechanical loading modes. Whereas, the strut length
parameterization results were in relation L α σ in case of Model I and, L α 1/σ (L is
strut length) in case of Model II, under axial loads, while under three-point bending
and torsion loading modes L α σ for both models, under radial compression the
relations were L α 1/σ in case of Model I and, L α σ in case of Model II. The best
combination of strut dimension in the thickness case was t4 = 230 µm for both models,
in strut width were w3=0.180, and w4= 0.250 mm for Model I and Model II,
respectively, and in strut length were l2= 1.40, and l2= 1.75 mm for Model I and Model
II, respectively. In conclusions, the mathematical selection approach and the consistent
mathematical approach of MCDM has been proposed, also the mechanical
performance has been improved for parameterized stent models
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