Search results for: 3D volumetric reconstruction

Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

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Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

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When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, customization, reverse engineering, weighted morphing, shape blending

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

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Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

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Authors: Samuel Mejorado

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C. Reinahrdtii serves as one of the most promising organisms from which to obtain biological hydrogen. However, its production catalyst, [FeFe]-hydrogenase, is largely inhibited by the presence of oxygen. In recent years, researchers have identified a Proton Gradient Regulation 5 (PGR5) deficient mutant, which shows enhanced respiration and lower accumulations of oxygen within the system. In this research, we investigated the effects of varying nutrient conditions on PGR5 mutants' ability to produce hydrogen. After growing PGR5 mutants in varying nutrient conditions under 55W fluorescent lamps at 30℃ with constant stirring at 200 rpm, a common water displacement method was utilized to obtain a definitive volumetric reading of hydrogen produced by these mutants over a period of 12 days. After the trials, statistical t-tests and ANOVAs were performed to better determine the effect which nutrient conditions have on PGR5 mutants' ability to produce hydrogen. In this, we report that conditions of sulfur deprivation most optimally enhanced hydrogen production within these mutants, with groups grown under these conditions demonstrating the highest production capacity over the entire 12-day period. Similarly, it was found that when grown under conditions of nitrogen deprivation, a favorable shift towards carbon fixation and overall lipid/starch metabolism was observed. Overall, these results demonstrate that PGR5-deficient mutants stand as a promising source of biohydrogen when grown under conditions of sulfur deprivation. To date, photochemical characteristics of [FeFe]-hydrogenase in these mutants have yet to be investigated under conditions of sulfur deprivation.

Keywords: biofuel, biohydrogen, [FeFe]-hydrogenase, algal biofuel

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Authors: Saskya E. Carrera P., Ben Hankamer, Melanie Oey

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The green alga C. reinhardtii provides a platform for the cheap, scalable, and safe production of complex proteins. Despite gene expression in photosynthetic organisms being tightly regulated by light, most expression studies have analysed chloroplast recombinant protein production under constant light. Here the influence of illumination time and intensity on GFP and a GFP-PlyGBS (bacterial-lysin) fusion protein expression was investigated. The expression of both proteins was strongly influenced by the light regime (6-24 hr illumination per day), the light intensity (0-450 E m⁻²s⁻¹) and growth condition (photoautotrophic, mixotrophic and heterotrophic). Heterotrophic conditions resulted in relatively low recombinant protein yields per unit volume, despite high protein yields per cell, due to low growth rates. Mixotrophic conditions exhibited the highest yields at 6 hrs illumination at 200µE m⁻²s⁻¹ and under continuous low light illumination (13-16 mg L⁻¹ GFP and 1.2-1.6 mg L⁻¹ GFP-PlyGBS), as these conditions supported good cell growth and cellular protein yields. A ~23-fold increase in protein accumulation per cell and ~9-fold increase L⁻¹ culture was observed compared to standard constant 24 hr illumination for GFP-PlyGBS. The highest yields under photoautotrophic conditions were obtained under 9 hrs illumination (6 mg L⁻¹ GFP and 2.1 mg L⁻¹ GFP-PlyGBS). This represents a ~4-fold increase in cellular protein accumulation for GFP-PlyGBS. On a volumetric basis the highest yield was at 15 hrs illumination (~2-fold increase L⁻¹ over the constant light for GFP-PlyGBS). Optimising illumination conditions to balance growth and protein expression can thus significantly enhance overall recombinant protein production in C. reinhardtii cultures.

Keywords: chlamydomonas reinhardtii, light, mixotrophic, recombinant protein

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

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Authors: Georgeta Voicu, Cristina Daniela Ghitulica, Andreia Cucuruz, Cristina Busuioc

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In the field of tissue engineering, the compositional and microstructural features of the employed materials play an important role, with implications on the mechanical and biological behaviour of the medical devices. In this context, the development of apatite - natural biopolymer composites represents a choice of many scientific groups. Thus, hydroxyapatite powders were synthesized by a wet method, namely co-precipitation, starting from high purity reagents (CaO, MgO, and H3PO4). Moreover, the substitution of calcium with magnesium have been approached, in the 5 - 10 wt.% range. Afterward, the phosphate powders were integrated in two types of composites with chitosan, different from morphological point of view. First, 3D porous scaffolds were obtained by a freeze-drying procedure. Second, uniform, compact films were achieved by film casting. The influence of chitosan molecular weight (low, medium and high), as well as apatite powder to polymer ratio (1:1 and 1:2) on the morphological properties, were analysed in detail. In conclusion, the reported biocomposites, prepared by a straightforward route are suitable for bone substitution or repairing applications.

Keywords: bone reconstruction, chitosan, composite scaffolds, hydroxyapatite

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Authors: Madalina Postaru, Alexandra Tucaliuc, Dan Cascaval, Anca Irina Galaction

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Ergosterol (ergosta-5,7,22-trien-3β-ol) is the precursor of vitamin D2 (ergocalciferol), known as provitamin D2 as it is converted under UV radiation to this vitamin. The natural sources of ergosterol are mainly the yeasts (Saccharomyces sp., Candida sp.), but it can be also found in fungus (Claviceps sp.) or plants (orchids). As ergosterol is mainly accumulated in yeast cell membranes, especially in free form in the plasma-membrane, and the chemical synthesis of ergosterol does not represent an efficient method for its production, this study aimed to analyze the influence of aeration efficiency on ergosterol production by S. cerevisiae in batch and fed-batch fermentations, by considering different levels of mixing intensity, aeration rate, and n-dodecane concentration. Our previous studies on ergosterol production by S. cerevisiae in batch and fed-batch fermentation systems indicated that the addition of n-dodecane led to the increase of almost 50% of this sterol concentration, the highest productivity being reached for the fed-batch process. The experiments were carried out in a laboratory stirred bioreactor, provided with computer-controlled and recorded parameters. In batch fermentation system, the study indicated that the oxygen mass transfer coefficient, kLa, is amplified for about 3 times by increasing the volumetric concentration of n-dodecane from 0 to 15%. Moreover, the increase of dissolved oxygen concentration by adding n-dodecane leads to the diminution for 3.5 times of the produced alcohol amount. In fed-batch fermentation process, the positive influence of hydrocarbon on oxygen transfer rate is amplified mainly at its higher concentration level, as the result of the increased yeasts cells amount. Thus, by varying n-dodecane concentration from 0 to 15% vol., the kLa value increase becomes more important than for the batch fermentation, being of 4 times

Keywords: ergosterol, yeast fermentation, n-dodecane, oxygen-vector

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Authors: Ashraf Shebl, Bassam Garah, Radah Youssef

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Sexual assault is usually a hidden crime where the only witnesses are the victim and the assailant. For a variety of reasons, even the victim may be unable to provide a detailed account of the assault or the identity of the perpetrator. Often the case history deteriorates into one person’s word against another. With such limited initial information, the physical and biological evidence collected from the victim, from the crime scene, and from the suspect will play a pivotal role in the objective and scientific reconstruction of the events in question. The aim of work is to examine whether DNA profiles could be recovered from repeated washed clothes after contaminated by semen stains. Fresh semen about 1ml. ( <1 h old) taken from donor was deposited on four types of clothes (cotton, silk, polyester, and jeans). Then leave to dry in room temperature and washed by washing machine at temperature (30°C-60°C) and by hand washing. Some items of clothing were washed once, some twice and others three times. DNA could be extracted from some of these samples even after multiple washing. This study demonstrates that complete DNA profiles can be obtained from washed semen stains on different types of clothes, even after many repeated washing. These results indicated that clothes of the victims must be examined even if they were washed many times.

Keywords: sexual assault, DNA, persistence, clothes

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Authors: K. Rhea Devaiah, B. S. Premalatha

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Background: Tonsillar Lingual sulcus is the area between the tonsils and the base of the tongue. The surgical resection of the lesions in the head and neck results in changes in speech and swallowing functions. The severity of the speech and swallowing problem depends upon the site and extent of the lesion, types and extent of surgery and also the flexibility of the remaining structures. Need of the study: This paper focuses on the importance of speech and swallowing rehabilitation in an individual with the lesion in the Tonsillar Lingual Sulcus and post-operative functions. Aim: Evaluating the speech and swallow functions post-intensive speech and swallowing rehabilitation. The objectives are to evaluate the speech intelligibility and swallowing functions after intensive therapy and assess the quality of life. Method: The present study describes a report of an individual aged 47years male, with the diagnosis of basaloid squamous cell carcinoma, left tonsillar lingual sulcus (pT2n2M0) and underwent wide local excision with left radical neck dissection with PMMC flap reconstruction. Post-surgery the patient came with a complaint of reduced speech intelligibility, and difficulty in opening the mouth and swallowing. Detailed evaluation of the speech and swallowing functions were carried out such as OPME, articulation test, speech intelligibility, different phases of swallowing and trismus evaluation. Self-reported questionnaires such as SHI-E(Speech handicap Index- Indian English), DHI (Dysphagia handicap Index) and SESEQ -K (Self Evaluation of Swallowing Efficiency in Kannada) were also administered to know what the patient feels about his problem. Based on the evaluation, the patient was diagnosed with pharyngeal phase dysphagia associated with trismus and reduced speech intelligibility. Intensive speech and swallowing therapy was advised weekly twice for the duration of 1 hour. Results: Totally the patient attended 10 intensive speech and swallowing therapy sessions. Results indicated misarticulation of speech sounds such as lingua-palatal sounds. Mouth opening was restricted to one finger width with difficulty chewing, masticating, and swallowing the bolus. Intervention strategies included Oro motor exercise, Indirect swallowing therapy, usage of a trismus device to facilitate mouth opening, and change in the food consistency to help to swallow. A practice session was held with articulation drills to improve the production of speech sounds and also improve speech intelligibility. Significant changes in articulatory production and speech intelligibility and swallowing abilities were observed. The self-rated quality of life measures such as DHI, SHI and SESE Q-K revealed no speech handicap and near-normal swallowing ability indicating the improved QOL after the intensive speech and swallowing therapy. Conclusion: Speech and swallowing therapy post carcinoma in the tonsillar lingual sulcus is crucial as the tongue plays an important role in both speech and swallowing. The role of Speech-language and swallowing therapists in oral cancer should be highlighted in treating these patients and improving the overall quality of life. With intensive speech-language and swallowing therapy post-surgery for oral cancer, there can be a significant change in the speech outcome and swallowing functions depending on the site and extent of lesions which will thereby improve the individual’s QOL.

Keywords: oral cancer, speech and swallowing therapy, speech intelligibility, trismus, quality of life

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Authors: Varun Kumar, Chandra Shakher

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Micro-optical components such as microlenses and microlens array have numerous engineering and industrial applications for collimation of laser diodes, imaging devices for sensor system (CCD/CMOS, document copier machines etc.), for making beam homogeneous for high power lasers, a critical component in Shack-Hartmann sensor, fiber optic coupling and optical switching in communication technology. Also micro-optical components have become an alternative for applications where miniaturization, reduction of alignment and packaging cost are necessary. The compliance with high-quality standards in the manufacturing of micro-optical components is a precondition to be compatible on worldwide markets. Therefore, high demands are put on quality assurance. For quality assurance of these lenses, an economical measurement technique is needed. For cost and time reason, technique should be fast, simple (for production reason), and robust with high resolution. The technique should provide non contact, non-invasive and full field information about the shape of micro- optical component under test. The interferometric techniques are noncontact type and non invasive and provide full field information about the shape of the optical components. The conventional interferometric technique such as holographic interferometry or Mach-Zehnder interferometry is available for characterization of micro-lenses. However, these techniques need more experimental efforts and are also time consuming. Digital holography (DH) overcomes the above described problems. Digital holographic microscopy (DHM) allows one to extract both the amplitude and phase information of a wavefront transmitted through the transparent object (microlens or microlens array) from a single recorded digital hologram by using numerical methods. Also one can reconstruct the complex object wavefront at different depths due to numerical reconstruction. Digital holography provides axial resolution in nanometer range while lateral resolution is limited by diffraction and the size of the sensor. In this paper, Mach-Zehnder based digital holographic interferometric microscope (DHIM) system is used for the testing of transparent microlenses. The advantage of using the DHIM is that the distortions due to aberrations in the optical system are avoided by the interferometric comparison of reconstructed phase with and without the object (microlens array). In the experiment, first a digital hologram is recorded in the absence of sample (microlens array) as a reference hologram. Second hologram is recorded in the presence of microlens array. The presence of transparent microlens array will induce a phase change in the transmitted laser light. Complex amplitude of object wavefront in presence and absence of microlens array is reconstructed by using Fresnel reconstruction method. From the reconstructed complex amplitude, one can evaluate the phase of object wave in presence and absence of microlens array. Phase difference between the two states of object wave will provide the information about the optical path length change due to the shape of the microlens. By the knowledge of the value of the refractive index of microlens array material and air, the surface profile of microlens array is evaluated. The Sag of microlens and radius of curvature of microlens are evaluated and reported. The sag of microlens agrees well within the experimental limit as provided in the specification by the manufacturer.

Keywords: micro-optics, microlens array, phase map, digital holographic interferometric microscopy

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Mohamed Hassan Abdullahi

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Decomposition is used as a synthesis tool in several physical systems. It can also be used for tearing and restructuring, which is large-scale system analysis. On the other hand, the commutativity of series-connected systems has fascinated the interest of researchers, and its advantages have been emphasized in the literature. The presentation looks into the necessary conditions for decomposing any third-order discrete-time linear time-varying system into a commutative pair of first- and second-order systems. Additional requirements are derived in the case of nonzero initial conditions. MATLAB simulations are used to verify the findings. The work is unique and is being published for the first time. It is critical from the standpoints of synthesis and/or design. Because many design techniques in engineering systems rely on tearing and reconstruction, this is the process of putting together simple components to create a finished product. Furthermore, it is demonstrated that regarding sensitivity to initial conditions, some combinations may be better than others. The results of this work can be extended for the decomposition of fourth-order discrete-time linear time-varying systems into lower-order commutative pairs, as two second-order commutative subsystems or one first-order and one third-order commutative subsystems.

Keywords: commutativity, decomposition, discrete time-varying systems, systems

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Authors: Nicolas Cuevas-Alvear

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The subject of this paper is the concept of interpretation. Its purpose is to expose the need for a new concept of interpretation and to trace the construction route of interpretation as determination and negotiation. The thesis it defends is that interpretation is the determination of events and the negotiation of those determinations in communication. To meet its objective, this manuscript is divided into five sections. The first section introduces the subject and the need for a new concept of interpretation. The second section explicitly formulates the research questions and the objectives of the project for the construction of a new concept of interpretation. The third section presents the state of the art, specifically, the theory of Radical interpretation proposed by Donald Davidson and the theory of the Hermeneutic Circle proposed by Hans Georg Gadamer. In addition, in this section, there is a reconstruction of Ernst Cassirer's explanation of language as a symbolic form. The fourth section is an explanation of the proposal based on the theories presented. Specifically: language as a symbolic form explains interpretation as a determination of events using objective, subjective and intersubjective elements, and these three elements are negotiated in interpretation as communication. The last section is the bibliography proposed to carry out the project.

Keywords: interpretation, metaphysics, semantics, Donald Davidson, ERNST Cassirer

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Authors: Muhammad Tariq A. Chaudhary

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The tremendous loss of life that resulted in the aftermath of recent earthquakes in developing countries is mostly due to the collapse of non-engineered and semi-engineered building structures. Such structures are used as houses, schools, primary healthcare centres and government offices. These building are classified structurally into two categories viz. non-engineered and semi-engineered. Non-engineered structures include: adobe, Unreinforced Masonry (URM) and wood buildings. Semi-engineered buildings are mostly low-rise (up to 3 story) light concrete frame structures or masonry bearing walls with reinforced concrete slab. This paper presents an overview of the typical damage observed in non-engineered structures and their most likely causes in the past earthquakes with specific emphasis on the performance of such structures in the 2005 Kashmir earthquake. It is demonstrated that seismic performance of these structures can be improved from life-safety viewpoint by adopting simple low-cost modifications to the existing construction practices. Incorporation of some of these practices in the reconstruction efforts after the 2005 Kashmir earthquake are examined in the last section for mitigating seismic risk hazard.

Keywords: Kashmir earthquake, non-engineered buildings, seismic hazard, structural details, structural strengthening

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Authors: Juan Manuel Macia

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The Montreal Port Authority (MPA) wanted to build a new road link via Souligny Avenue to increase the fluidity of goods transported by truck in the Viau Street area of Montreal and to mitigate the current traffic problems on Notre-Dame Street. With the purpose of having a better integration and acceptance of this project with the neighboring residential surroundings, this project needed to include an architectural integration, bringing some artistic components to the bridge design along with some landscaping components. The MPA is required primarily to provide direct truck access to Port of Montreal with a direct connection to the future Assomption Boulevard planned by the City of Montreal and, thus, direct access to Souligny Avenue. The MPA also required other key aspects to be considered for the proposal and development of the project, such as the layout of road and rail configurations, the reconstruction of underground structures, the relocation of power lines, the installation of lighting systems, the traffic signage and communication systems improvement, the construction of new access ramps, the pavement reconstruction and a summary assessment of the structural capacity of an existing service tunnel. The identification of the various possible scenarios began by identifying all the constraints related to the numerous infrastructures located in the area of the future link between the port and the future extension of Souligny Avenue, involving interaction with several disciplines and technical specialties. Several viaduct- and tunnel-type geometries were studied to link the port road to the right-of-way north of Notre-Dame Street and to improve traffic flow at the railway corridor. The proposed design took into account the existing access points to Port of Montreal, the built environment of the MPA site, the provincial and municipal rights-of-way, and the future Notre-Dame Street layout planned by the City of Montreal. These considerations required the installation of an engineering structure with a span of over 60 m to free up a corridor for the future urban fabric of Notre-Dame Street. The best option for crossing this span length was identified by the design and construction of a curved bridge over Notre-Dame Street, which is essentially a structure with a deck formed by a reinforced concrete slab on steel box girders with a single span of 63.5m. The foundation units were defined as pier-cap type abutments on drilled shafts to bedrock with rock sockets, with MSE-type walls at the approaches. The configuration of a single-span curved structure posed significant design and construction challenges, considering the major constraints of the project site, a design for durability approach, and the need to guarantee optimum performance over a 75-year service life in accordance with the client's needs and the recommendations and requirements defined by the standards used for the project. These aspects and the need to include architectural and artistic components in this project made it possible to design, build, and integrate a signature infrastructure project with a sustainable approach, from which the MPA, the commuters, and the city of Montreal and its residents will benefit.

Keywords: curved bridge, steel box girder, medium span, simply supported, industrial and urban environment, architectural integration, design for durability

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

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Authors: Muhammad Zahid

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The mechanical process of smoothing and compressing a molten material by passing it through a number of pairs of heated rolls in order to produce a sheet of desired thickness is called calendering. The rolls that are in combination are called calenders, a term derived from kylindros the Greek word for the cylinder. It infects the finishing process used on cloth, paper, textiles, leather cloth, or plastic film and so on. It is a mechanism which is used to strengthen surface properties, minimize sheet thickness, and yield special effects such as a glaze or polish. It has a wide variety of applications in industries in the manufacturing of textile fabrics, coated fabrics, and plastic sheeting to provide the desired surface finish and texture. An analysis has been presented for the calendering of Pseudoplastic material. The lubrication approximation theory (LAT) has been used to simplify the equations of motion. For the investigation of the nature of the steady solutions that exist, we make use of the combination of exact solution and numerical methods. The expressions for the velocity profile, rate of volumetric flow and pressure gradient are found in the form of exact solutions. Furthermore, the quantities of interest by engineering point of view, such as pressure distribution, roll-separating force, and power transmitted to the fluid by the rolls are also computed. Some results are shown graphically while others are given in the tabulated form. It is found that the non-Newtonian parameter and Reynolds number serve as the controlling parameters for the calendering process.

Keywords: calendering, exact solutions, lubrication approximation theory, numerical solutions, pseudoplastic material

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Authors: G. Purushotham, Joel Hemanth

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An investigation has been carried out to fabricate and evaluate the strength and soundness of chilled composites consisting of nickel matrix and fused silica particles (size 40–150 μm) in the matrix. The dispersoid added ranged from 3 to 12 wt. % in steps of 3%. The resulting composites cast in moulds containing metallic and non-metallic chill blocks (MS, SiC, and Cu) were tested for their microstructure and mechanical properties. The main objective of the present research is to obtain fine grain Ni/SiO2 chilled sound composite having very good mechanical properties. Results of the investigation reveal the following: (1) Strength of the composite developed is highly dependent on the location of the casting from where the test specimens are taken and also on the dispersoid content of the composite. (2) Chill thickness and chill material, however, does significantly affect the strength and soundness of the composite. (3) Soundness of the composite developed is highly dependent on the chilling rate as well as the dispersoid content. An introduction of chilling and increase in the dispersoid content of the material both result in an increase in the ultimate tensile strength (UTS) of the material. The temperature gradient developed during solidification and volumetric heat capacity (VHC) of the chill used is the important parameters controlling the soundness of the composite. (4) Thermal properties of the end chills are used to determine the magnitude of the temperature gradient developed along the length of the casting solidifying under the influence of chills.

Keywords: metal matrix composite, mechanical properties, corrosion behavior, nickel alloy, fused silica, chills

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Jianjun Wu, Fanhui Guo, Yixin Zhang

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In this study, gasification-coke were produced by blending the middlings (MC), and coking coal (CC) and a large proportion of long flame coal (Shenfu coal, SC), the effects of blending ratio were investigated. Mineral evolution and crystalline order obtained by XRD methods were reproduced within reasonable accuracy. Structure characteristics of partially gasification-coke such as surface area and porosity were determined using the N₂ adsorption and mercury porosimetry. Experimental data of gasification-coke was dominated by the TGA results provided trend, reactivity differences between gasification-cokes are discussed in terms of structure characteristic, crystallinity, and alkali index (AI). The first-order reaction equation was suitable for the gasification reaction kinetics of CO₂ atmosphere which was represented by the volumetric reaction model with linear correlation coefficient above 0.985. The differences in the microporous structure of gasification-coke and catalysis caused by the minerals in parent coals were supposed to be the main factors which affect its reactivity. The addition of MC made the samples enriched with a large amount of ash causing a higher surface area and a lower crystalline order to gasification-coke which was beneficial to gasification reaction. The higher SiO₂ and Al₂O₃ contents, causing a decreasing AI value and increasing activation energy, which reduced the gasification reaction activity. It was found that the increasing amount of MC got a better performance on the coke gasification reactivity by blending > 30% SC with this coking process.

Keywords: low-rank coal, middlings, structure characteristic, mineral evolution, alkali index, gasification-coke, gasification kinetics

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

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Authors: Varsha Rainson

Abstract:

Artificial intelligence (AI) has great potential and can be used as a powerful tool of application in various domains and sectors. But with the application of AI, there comes a wide spectrum of concerns around bias, accountability, transparency, and privacy. Hence, there is a need for responsible AI, which can uphold ethical and accountable practices to ensure that things are transparent and fair. The paper is a combination of AI and cultural heritage preservation, with a greater focus on India because of the rich cultural legacy that it holds. India’s cultural heritage in itself contributes to its identity and the economy. In this paper, along with discussing the impact culture holds on the Indian economy, we will discuss the threats that the cultural heritage is exposed to due to pollution, climate change and urbanization. Furthermore, the paper reviews some of the exciting applications of AI in cultural heritage preservation, such as 3-D scanning, photogrammetry, and other techniques which have led to the reconstruction of cultural artifacts and sites. The paper eventually moves into the potential risks and challenges that AI poses in cultural heritage preservation. These include ethical, legal, and social issues which are to be addressed by organizations and government authorities. Overall, the paper strongly argues the need for responsible AI and the important role it can play in preserving India’s cultural heritage while holding importance to value and diversity.

Keywords: responsible AI, cultural heritage, artificial intelligence, biases, transparency

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Authors: A. Kherraf, S. Ouarrak, L. Azzouzi, R. Habbal

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Introduction: Preserved LVEF heart failure is an important cause of mortality and morbidity in hypertensive patients. A strong correlation between impaired diastolic function and longitudinal systolic dysfunction. could have several explanations, first, the diastole is an energy dependent process, especially during its first phase, it also includes active systolic components during the phase of iso volumetric relaxation, in addition, the impairment of the intrinsic myocytic function is part of hypertensive pathology as evidenced by recent studies. METHODS AND MATERIALS: This work consists of performing in a series of 333 hypertensive patients (aged 25 to 75 years) a complete echocardiographic study, including LVEF by Simpson biplane method, the calculation of the indexed left ventricular mass, the analysis of the diastolic function, and finally, the study of the longitudinal deformation of the LV by the technique of speckletracking (calculation of the GLS). Patients with secondary hypertension, leaky or stenosing valve disease, arrhythmia, and a history of coronary insufficiency were excluded from this study. RESULTS: Of the 333 hypertensive patients, 225 patients (67.5%) had impaired diastolic function, of which 60 patients (18%) had high filling pressures. 49.39% had echocardigraphic HVG, Almost all of these patients (60 patients) had low GLS. There is a statistically very significant relationship between lower GLS and increased left ventricular filling pressures in hypertensive patients. These results suggest that increased filling pressures are closely associated with atrioventricular interaction in patients with hypertension, with a strong correlation with impairment of longitudinal systolic function and diastolic function CONCLUSION: Overall, a linear relationship is established between increased left ventricular mass, diastolic dysfunction, and longitudinal LV systolic dysfunction

Keywords: hypertension, diastolic function, left ventricle, heart failure

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Authors: Maryam Sadeghi, Claude Bazin, Daniel Hodouin, Laura Perez Barnuevo

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The performance of a separation process is usually evaluated using performance indices calculated from elemental assays readily available from the chemical analysis laboratory. However, the separation process performance is essentially related to the properties of the minerals that carry the elements and not those of the elements. Since elements or metals can be carried by valuable and gangue minerals in the ore and that each mineral responds differently to a mineral processing method, the use of only elemental assays could lead to erroneous or uncertain conclusions on the process performance. This paper discusses the advantages of using performance indices calculated from minerals content, such as minerals recovery, for process performance assessments. A method is presented that uses elemental assays to estimate the minerals content of the solids in various process streams. The method combines the stoichiometric composition of the minerals and constraints of mass conservation for the minerals through the concentration process to estimate the minerals content from elemental assays. The advantage of assessing a concentration process using mineral based performance indices is illustrated for an iron ore concentration circuit.

Keywords: data reconciliation, iron ore concentration, mineral composition, process performance assessment

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Authors: Yenni Kurniawati

Abstract:

Students Prediction Skill in chemistry experiments is an important skill for pre-service chemistry students to stimulate students reflective thinking at each stage of many chemistry experiments, qualitatively and quantitatively. A Virtual Chemistry Laboratory was designed to give students opportunities and times to practicing many kinds of chemistry experiments repeatedly, everywhere and anytime, before they do a real experiment. The Virtual Chemistry Laboratory content was constructed using the Model of Educational Reconstruction and developed to enhance students ability to predicted the experiment results and analyzed the cause of error, calculating the accuracy and precision with carefully in using chemicals. This research showed students changing in making a decision and extremely beware with accuracy, but still had a low concern in precision. It enhancing students level of reflective thinking skill related to their prediction skill 1 until 2 stage in average. Most of them could predict the characteristics of the product in experiment, and even the result will going to be an error. In addition, they take experiments more seriously and curiously about the experiment results. This study recommends for a different subject matter to provide more opportunities for students to learn about other kinds of chemistry experiments design.

Keywords: virtual chemistry laboratory, chemistry experiments, prediction skill, pre-lab experiences

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Bartlomiej Przybyszewski, Rafal Kozera, Katarzyna Zolynska, Anna Boczkowska, Daria Pakula

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The build-up and accumulation of dirt, ice, and snow on structural elements and vehicles is an unfavorable phenomenon, leading to economic losses and often also posing a threat to people. This problem occurs wherever the use of polymer coatings has become a standard, among others in photovoltaic farms, aviation, wind energy, and civil engineering. The accumulated pollution on the photovoltaic modules can reduce their efficiency by several percent, and snow stops power production. Accumulated ice on the blades of wind turbines or the wings of airplanes and drones disrupts the airflow by changing their shape, leading to increased drag and reduced efficiency. This results in costly maintenance and repairs. The goal of the work is to reduce or completely eliminate the accumulation of dirt, snow, and ice build-up on polymer coatings by achieving self-cleaning and icephobic properties. It is done by the use of a multi-step surface modification of the polymer nanocoatings. For this purpose, two methods of surface structuring and the preceding volumetric modification of the chemical composition with proprietary organosilicon compounds and/or mineral additives were used. To characterize the surface topography of the modified coatings, light profilometry was utilized. Measurements of the wettability parameters (static contact angle and contact angle hysteresis) on the investigated surfaces allowed to identify their wetting behavior and determine relation between hydrophobic and anti-icing properties. Ice adhesion strength was measured to assess coatings' anti-icing behavior.

Keywords: anti-icing properties, self-cleaning, polymer coatings, icephobic coatings

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