Search results for: thermomechanical processing

Authors: Natalia Fijol, Aji P. Mathew

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We present the processing and characterisation of three-dimensional (3D) monolith filters based on polylactic acid (PLA) reinforced with various nature-derived nanospecies such as hydroxyapatite, modified cellulose fibers and chitin fibers. The nanospecies of choice were dispersed in PLA through Thermally Induced Phase Separation (TIPS) method. The biocomposites were developed via solvent-assisted blending and the obtained pellets were further single-screw extruded into 3D-printing filaments and processed into various geometries using Fused Deposition Modelling (FDM) technique. The printed prototypes included cubic, cylindrical and hour-glass shapes with diverse patterns of printing infill as well as varying pore structure including uniform and multiple level gradual pore structure. The pores and channel structure as well as overall shape of the prototypes were designed in attempt to optimize the flux and maximize the adsorption-active time. FDM is a cost and energy-efficient method, which does not require expensive tools and elaborated post-processing maintenance. Therefore, FDM offers the possibility to produce customized, highly functional water purification filters with tuned porous structures suitable for removal of wide range of common water pollutants. Moreover, as 3D printing becomes more and more available worldwide, it allows producing portable filters at the place and time where they are most needed. The study demonstrates preparation route for the PLA-based, fully biobased composite and their processing via FDM technique into water purification filters, addressing water treatment challenges on an industrial scale.

Keywords: fused deposition modelling, water treatment, biomaterials, 3D printing, nanocellulose, nanochitin, polylactic acid

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Authors: A. B. M. S. Hossain, A. Abdelgadir, N. A. Ibrahim

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Fresh ripen olive cannot be consumed immediately after harvest due to the excessive bitterness having polyphenol as antioxidant. Industrial processing needs to be edible the fruit. The laboratory processing technique has been used to make it edible by using acid (vinegar, 5% acetic acid) and alkaline solvent (NaOH). Based on the treatment and consequence, innovative data have been found in this regard. The experiment was conducted to investigate biochemical content, nutritional and DNA characterization of olive fruit treated with alkaline (Sodium chloride anhydrous) and acidic solvent (5% acetic acid, vinegar). The treatments were used as control (no water), water control, 10% sodium chloride anhydrous (NaOH), vinegar (5% acetic acid), vinegar + NaOH and vinegar + NaOH + hot water treatment. Our results showed that inverted sugar and glucose content were higher in the vinegar and NaOH treated olive than in other treatments. Fructose content was the highest in vinegar + NaOH treated fruit. Nutrient contents NO3 K, Ca and Na were found higher in the treated fruit than the control fruit. Moreover, maximum K content was observed in the case of all treatments compared to the other nutrient content. The highest acidic (lower pH) condition (sour) was found in treated fruit. DNA yield was found higher in water control than acid and alkaline treated olives. DNA band was wider in the olive treated water control compared to the NaOH, vinegar, vinegar + NaOH and vinegar + NaOH + Hot water treatment. Finally, results suggest that vinegar + NaOH treated olive fruit was the best for fresh olive homemade processing after harvesting for edible purpose.

Keywords: olive, vinegar, sugars, DNA band, bioprocess biotechnology

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Authors: Sihem Oujdi, Hafida Belbachir

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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Gajanan Bhat, Vincent Kandagor, Daniel Prather, Ramesh Bhave

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Polyetherimide (PEI), an engineering plastic with very high glass transition temperature and excellent chemical and thermal stability, has been processed into a controlled porosity filter media of varying pore size, performance, and surface characteristics. A special grade of the PEI was processed by melt blowing to produce microfiber nonwovens suitable as filter media. The resulting microfiber webs were characterized to evaluate their structure and properties. The fiber webs were further modified by hot pressing, a post processing technique, which reduces the pore size in order to improve the barrier properties of the resulting membranes. This ongoing research has shown that PEI can be a good candidate for filter media requiring high temperature and chemical resistance with good mechanical properties. Also, by selecting the appropriate processing conditions, it is possible to achieve desired filtration performance from this engineering plastic.

Keywords: nonwovens, melt blowing, polyehterimide, filter media, microfibers

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Authors: N. Metidji, O. Badaoui, A. Djebli, H. Bendjebbas, R. Sellami

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The agro-industry is considered as one of the most waste producing industrial fields as a result of food processing. Upgrading and reuse of these wastes as animal or poultry food seems to be a promising alternative. Combined with the use of clean energy resources, the recovery process would contribute more to the environment protection. It is in this framework that a new solar dryer has been designed in the Unit of Solar Equipment Development. Direct solar drying has, also, many advantages compared to natural sun drying. In fact, the first does not cause product degradation as it is protected by the drying chamber from direct sun, insects and exterior environment. The aim of this work is to study the drying kinetics of waste, generated during the processing of pepper, by using a direct natural convection solar dryer at 35◦C and 55◦C. The rate of moisture removal from the product to be dried has been found to be directly related to temperature, humidity and flow rate. The characterization of these parameters has allowed the determination of the appropriate drying time for this product namely peppers waste.

Keywords: solar energy, solar dryer, energy conversion, pepper drying, forced convection solar dryer

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Authors: Zhicheng Han

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This study examines the correlation between knowledge of formulaic language, working memory (WM), and phonological short-term memory (PSTM) in Chinese L2 learners of English. This study investigates if WM and PSTM correlate differently to the acquisition of formulaic language, which may be relevant for the discourse around the conceptualization of formulas. Connectionist approaches have lead scholars to argue that formulas are form-meaning connections stored whole, making PSTM significant in the acquisitional process as it pertains to the storage and retrieval of chunk information. Generativist scholars, on the other hand, argued for active participation of interlanguage grammar in the acquisition and use of formulaic language, where formulas are represented in the mind but retain the internal structure built around a lexical core. This would make WM, especially the processing component of WM an important cognitive factor since it plays a role in processing and holding information for further analysis and manipulation. The current study asked L1 Chinese learners of English enrolled in graduate programs in China to complete a preference raking task where they rank their preference for formulas, grammatical non-formulaic expressions, and ungrammatical phrases with and without the lexical core in academic contexts. Participants were asked to rank the options in order of the likeliness of them encountering these phrases in the test sentences within academic contexts. Participants’ syntactic proficiency is controlled with a cloze test and grammar test. Regression analysis found a significant relationship between the processing component of WM and preference of formulaic expressions in the preference ranking task while no significant correlation is found for PSTM or syntactic proficiency. The correlational analysis found that WM, PSTM, and the two proficiency test scores have significant covariates. However, WM and PSTM have different predictor values for participants’ preference for formulaic language. Both storage and processing components of WM are significantly correlated with the preference for formulaic expressions while PSTM is not. These findings are in favor of the role of interlanguage grammar and syntactic knowledge in the acquisition of formulaic expressions. The differing effects of WM and PSTM suggest that selective attention to and processing of the input beyond simple retention play a key role in successfully acquiring formulaic language. Similar correlational patterns were found for preferring the ungrammatical phrase with the lexical core of the formula over the ones without the lexical core, attesting to learners’ awareness of the lexical core around which formulas are constructed. These findings support the view that formulaic phrases retain internal syntactic structures that are recognized and processed by the learners.

Keywords: formulaic language, working memory, phonological short-term memory, academic language

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Authors: German Galvez-Garcia, Javier Albayay, Javiera Peña, Marta Lavin, George A. Michael

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The aim of this research was to investigate whether the selection of the actions needs different inhibition processes during the response selection stage. In Experiment 1, we compared the magnitude of the Spatial Stroop effect, which occurs in response selection stage, in two motor actions (lifting vs reaching) when the participants performed both actions in the same block or in different blocks (mixed block vs. pure blocks).Within pure blocks, we obtained faster latencies when lifting actions were performed, but no differences in the magnitude of the Spatial Stroop effect were observed. Within mixed block, we obtained faster latencies as well as bigger-magnitude for Spatial Stroop effect when reaching actions were performed. We concluded that when no action selection is required (the pure blocks condition), inhibition works as a unitary system, whereas in the mixed block condition, where action selection is required, different inhibitory processes take place within a common processing stage. In Experiment 2, we investigated this common processing stage in depth by limiting participants’ available resources, requiring them to engage in a concurrent auditory task within a mixed block condition. The Spatial Stroop effect interacted with Movement as it did in Experiment 1, but it did not significantly interact with available resources (Auditory task x Spatial Stroop effect x Movement interaction). Thus, we concluded that available resources are distributed equally to both inhibition processes; this reinforces the likelihood of there being a common processing stage in which the different inhibitory processes take place.

Keywords: inhibition process, motor processes, selective inhibition, dual task

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Farzad Vakili-Farahani, Joern Lungershausen, Kilian Wasmer

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Wobbled laser beam welding, fast oscillations of a tiny laser beam within a designed path (weld geometry) during the laser pulse illumination, opens new possibilities to improve the marco-to micro-manufacturing process. The present work introduces the wobbled laser beam welding as a robust welding strategy for improving macro-to micro-fabrication process, e.g., the laser processing for gap-bridging and packaging industry. The typical requisites and relevant equipment for the development of a wobbled laser processing unit are addressed, including a suitable laser source, light delivery system, optics, proper beam deflection system and the design geometry. In addition, experiments have been carried out on titanium plate to compare the results of wobbled laser welding with conventional pulsed laser welding. As compared to the pulsed laser welding, the wobbled laser welding offers a much greater fusion area (i.e. additional molten material) while minimizing the HAZ and provides a better confinement of the material microstructural changes.

Keywords: wobbled laser beam welding, wobbling function, beam oscillation, micro welding

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Authors: Boce Zhang

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Strategic innovation of nanotechnology to promote food safety has drawn tremendous attentions among research groups, which includes the need for research support during the implementation of the Food Safety Modernization Act (FSMA) in the United States. There are urgent demands and knowledge gaps to the understanding of a) food-water-bacteria interface as for how pathogens persist and transmit during food processing and storage; b) minimum processing requirement needed to prevent pathogen cross-contamination in the food system. These knowledge gaps are of critical importance to the food industry. However, the lack of knowledge is largely hindered by the limitations of research tools. Our groups recently endeavored two novel engineering systems with biomimetics and microfluidics as a holistic approach to hazard analysis and risk mitigation, which provided unprecedented research opportunities to study pathogen behavior, in particular, contamination, and cross-contamination, at the critical food-water-pathogen interface. First, biomimetically-patterned surfaces (BPS) were developed to replicate the identical surface topography and chemistry of a natural food surface. We demonstrated that BPS is a superior research tool that empowers the study of a) how pathogens persist through sanitizer treatment, b) how to apply fluidic shear-force and surface tension to increase the vulnerability of the bacterial cells, by detaching them from a protected area, etc. Secondly, microfluidic devices were designed and fabricated to study the bactericidal kinetics in the sub-second time frame (0.1~1 second). The sub-second kinetics is critical because the cross-contamination process, which includes detachment, migration, and reattachment, can occur in a very short timeframe. With this microfluidic device, we were able to simulate and study these sub-second cross-contamination scenarios, and to further investigate the minimum sanitizer concentration needed to sufficiently prevent pathogen cross-contamination during the food processing. We anticipate that the findings from these studies will provide critical insight on bacterial behavior at the food-water-cell interface, and the kinetics of bacterial inactivation from a broad range of sanitizers and processing conditions, thus facilitating the development and implementation of science-based food safety regulations and practices to mitigate the food safety risks.

Keywords: biomimetic materials, microbial food safety, microfluidic device, nanotechnology

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Authors: Mobarok Hossain Bhuyain

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Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.

Keywords: human detection, target tracking, neural network, particle filter

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Authors: Mamdouh Yousef Saleh, Medhat Hosny El-Zahar, Shymaa El-Dosoky

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In most cases, the associated processing cost of dewatering sludge increase with the solid particles concentration. All experiments in this study were conducted on biological sludge type. All experiments help to reduce the greenhouse gases in addition, the technology used was faster in time and less in cost compared to other methods. First, the bubbling pressure was used to dissolve N₂ gas into the sludge, second alum was added to accelerate the process of coagulation of the sludge particles and facilitate their flotation, and third nitrogen gas was used to help floating the sludge particles and reduce the processing time because of the nitrogen gas from the inert gases. The conclusions of this experiment were as follows: first, the best conditions were obtained when the bubbling pressure was 0.6 bar. Second, the best alum dose was determined to help the sludge agglomerate and float. During the experiment, the best alum dose was 80 mg/L. It increased concentration of the sludge by 7-8 times. Third, the economic dose of nitrogen gas was 60 mg/L with separation efficiency of 85%. The sludge concentration was about 8-9 times. That happened due to the gas released tiny bubbles which adhere to the suspended matter causing them to float to the surface of the water where it could be then removed.

Keywords: nitrogen gas, biological treatment, alum, dewatering sludge, greenhouse gases

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Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

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Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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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: Mark Lokanan

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The paper analyzes the processing of complaints against investment brokers and dealer members through the Investment Industry Regulatory Organization of Canada (IIROC) from 2008 to 2017. IIROC is the self-regulatory organization (SRO) that is responsible for policing investment dealers and brokerage firms that trade in Canada’s securities market. Data from the study came from IIROC's enforcement annual reports for the years examined. The case processing is evaluated base on the misconduct funnel that was originally designed for street crime and applies to the enforcement of investment fraud. The misconduct funnel is used as a framework to examine IIROC’s claim that it brought in more complaints (funnel in) than government regulators and shows how these complaints are funneled out and funneled away as they are processed through IIROC’s enforcement system. The results indicate that IIROC is ineffective in disciplining its members and is unable to handle the more serious quasi-criminal and improper sales practices offenses. It is hard not to see the results of the paper being used by the legislator in Ottawa to show the importance of a federal securities regulatory agency such as the Securities and Exchange Commission (SEC) in the United States.

Keywords: investment fraud, securities regulation, compliance, enforcement

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: Naman Jain, Shaun Fernandes

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With the increasing prevalence of online healthcare services, selecting the most suitable doctor has become a complex task, requiring careful consideration of both public sentiment and personal preferences. This paper proposes a sentiment analysis-driven method that integrates public reviews with user-specific criteria and correlated attributes to recommend online doctors. By leveraging Natural Language Processing (NLP) techniques, public sentiment is extracted from online reviews, which is then combined with user-defined preferences such as specialty, years of experience, location, and consultation fees. Additionally, correlated attributes like education and certifications are incorporated to enhance the recommendation accuracy. Experimental results demonstrate that the proposed system significantly improves user satisfaction by providing personalized doctor recommendations that align with both public opinion and individual needs.

Keywords: sentiment analysis, online doctors, personal preferences, correlated attributes, recommendation system, healthcare, natural language processing

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Authors: Jiří Kubásek, Peter Minárik, Klára Hosová, Stanislav Šašek, Jozef Veselý, Jitka Stráská, Drahomír Dvorský, Dalibor Vojtěch, Miloš Janeček

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Mg-2Y-2Gd-1Ca and Mg-4Y-4Gd-2Ca alloys were processed by extrusion or equal channel angular pressing (ECAP) to analyse the effect of the microstructure on ignition temperature, mechanical properties and corrosion resistance. The alloys are characterized by good mechanical properties and exceptionally high ignition temperature, which is a critical safety measure. The effect of extrusion and ECAP on the microstructure, mechanical properties and ignition temperature was studied. The obtained results indicated a substantial effect of the processing conditions on the average grain size, the recrystallized fraction and texture formation. Both alloys featured a high strength, depending on the composition and processing condition, and a high ignition temperature of ≈1100 °C (Mg-4Y-4Gd-2Ca) and ≈950 °C (Mg-2Y-2Gd-1Ca), which was attributed to the synergic effect of Y, Gd and Ca oxides, with the dominant effect of Y₂O₃. The achieved combination of enhanced mechanical properties and the ignition temperature makes these alloys a prominent candidate for aircraft applications.

Keywords: magnesium alloys, enhanced ignition temperature, mechanical properties, ECAP

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Authors: Nilamadhab Mohanty

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It is essential to use message formats that make communication understandable and correct. It is because; the information format can influence consumer decision on the purchase of a product. This study combines information from qualitative inquiry, media trend analysis, eye tracking experiment, and questionnaire data to examine the impact of specific message format and consumer perceived risk on attention to the information and risk retention. We investigated the influence of message framing (goal framing, attribute framing, and mix framing) on consumer memory, study time, and decisional uncertainty while deciding on the purchase of drugs. Furthermore, we explored the impact of consumer perceived risk (associated with the use of the drug, i.e., RISK-AB and perceived risk associated with the non-use of the drug, i.e., RISK-EB) on message format preference. The study used eye-tracking methods to understand the differences in message processing. Findings of the study suggest that the message format influences information processing, and participants' risk perception impacts message format preference. Eye tracking can be used to understand the format differences and design effective advertisements.

Keywords: message framing, consumer perceived risk, advertising, eye tracking

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Reza Sadeghi

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In this study, microwave heating was employed for controlling Oryzaephilus mercator. adults infesting stored Iranian dried fig. For this purpose, the dried fig samples were artificially infested with O. mercator and then heated in a microwave oven (2450 MHz) at the power outputs of 450, 720, and 900 W for 10, 20, 30, and 40 s, respectively. Subsequently, changes in the colors of the product samples under the effects of the varied microwave applications were investigated in terms of lightness (ΔL*), redness (Δa*), and yellowness (Δb*) using an image processing technique. The results revealed that both parameters of microwave power and exposure time had significant impacts on the pest mortality rates (p<0.01). In fact, a direct positive relationship was obtained between the mortality rate and microwave irradiation power. Complete mortality was achieved for the pest at the power of 900 W and exposure time of 40 s. The dried fig samples experienced fewer changes in their color parameters. Considering the successful pest control and acceptable changes in the product quality, microwave irradiation can be introduced as an appropriate alternative to chemical fumigants.

Keywords: colorimetric assay, microwave heating, Oryzaephilus mercator, mortality

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Authors: Alaa Alrakaf, Sk. Md. Mizanur Rahman

Abstract:

Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation.

Keywords: Arabic natural language processing, machine learning, machine translation, Naive bayes classifier, word sense disambiguation

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Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

Abstract:

A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

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Authors: N. Metidji, N. Kasbadji Merzouk, O. Badaoui, R. Sellami, A. Djebli

Abstract:

The Agro-industry is considered as one of the most waste producing industrial fields as a result of food processing. Upgrading and reuse of these wastes as animal or poultry food seems to be a promising alternative. Combined with the use of clean energy resources, the recovery process would contribute more to the environment protection. It is in this framework that a new solar dryer has been designed in the Unit of Solar Equipments Development. Indirect solar drying has, also, many advantages compared to natural sun drying. In fact, the first does not cause product degradation as it is protected by the drying chamber from direct sun, insects and exterior environment. The aim of this work is to study the drying kinetics of waste, generated during the processing of orange to make fruit juice, by using an indirect forced convection solar dryer at 50 °C and 60 °C, the rate of moisture removal from the product to be dried has been found to be directly related to temperature, humidity and flow rate. The characterization of these parameters has allowed the determination of the appropriate drying time for this product namely orange waste.

Keywords: solar energy, solar dryer, energy conversion, orange drying, forced convection solar dryer

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Authors: Taher El-Bitar, Maha El-Meligy, Eman El-Shenawy, Almosilhy Almosilhy, Nader Dawood

Abstract:

The steel contains 0.3% C and 0.004% B, beside Mn, Cr, Mo, and Ni. The alloy was processed by using 20-ton capacity electric arc furnace (EAF), and then refined by ladle furnace (LF). Liquid steel was cast as rectangular ingots. Dilatation test showed the critical transformation temperatures Ac₁, Ac₃, M_s and M_f as 716, 835, 356, and 218 °C. The ingots were austenitized and soaked and then rough rolled to thin slabs with 80 mm thickness. The thin slabs were then reheated and soaked for finish rolling to 6.0 mm thickness plates. During the rough rolling, the roll force increases as a result of rolling at temperatures less than recrystallization temperature. However, during finish rolling, the steel reflects initially continuous static recrystallization after which it shows strain hardening due to fall of temperature. It was concluded that, the steel plates were successfully heat treated by quenching-tempering at 250 ºC for 20 min.

Keywords: armor steel, austenitizing, critical transformation temperatures (CTTs), dilatation curve, martensite, quenching, rough and finish rolling processes, soaking, tempering, thermo-mechanical processing

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Authors: Yinheng Li

Abstract:

The remarkable advancements in large language models (LLMs) have brought about significant improvements in natural language processing tasks. This paper presents a comprehensive review of in-context learning techniques, focusing on different types of prompts, including discrete, continuous, few-shot, and zero-shot, and their impact on LLM performance. We explore various approaches to prompt design, such as manual design, optimization algorithms, and evaluation methods, to optimize LLM performance across diverse tasks. Our review covers key research studies in prompt engineering, discussing their methodologies and contributions to the field. We also delve into the challenges faced in evaluating prompt performance, given the absence of a single ”best” prompt and the importance of considering multiple metrics. In conclusion, the paper highlights the critical role of prompt design in harnessing the full potential of LLMs and provides insights into the combination of manual design, optimization techniques, and rigorous evaluation for more effective and efficient use of LLMs in various Natural Language Processing (NLP) tasks.

Keywords: in-context learning, prompt engineering, zero-shot learning, large language models

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Authors: Hasika Mith, Hassany Ly, Hengsim Phoung, Rathana Sovann, Pichmony Ek, Sokuntheary Theng

Abstract:

Rice is one of the most important crops used in the production of ready-to-cook (RTC) products such as rice vermicelli, noodles, rice paper, Banh Kanh, wine, snacks, and desserts. Meanwhile, extrusion is the most creative food processing method used for developing products with improved nutritional, functional, and sensory properties. This method authorizes process control such as mixing, cooking, and product shaping. Therefore, the objectives of this study were to produce rice vermicelli using a twin screw extruder, and the cooking properties of extruded rice vermicelli were investigated. Response Surface Methodology (RSM) with Box-Behnken design was applied to optimize extrusion conditions in order to achieve the most desirable product characteristics. The feed moisture rate (30–35%), the barrel temperature (90–110°C), and the screw speed (200–400 rpm) all play a big role and have a significant impact on the water absorption index (WAI), cooking yield (CY), and cooking loss (CL) of extrudate rice vermicelli. Results showed that the WAI of the final extruded rice vermicelli ranged between 216.97% and 571.90%. The CY ranged from 147.94 to 203.19%, while the CL ranged from 8.55 to 25.54%. The findings indicated that at a low screw speed or low temperature, there are likely to be more unbroken polymer chains and more hydrophilic groups, which can bind more water and make WAI values higher. The extruded rice vermicelli's cooking yield value had altered considerably after processing under various conditions, proving that the screw speed had little effect on each extruded rice vermicelli's CY. The increase in barrel temperature tended to increase cooking yield and reduce cooking loss. In conclusion, the extrusion processing by a twin-screw extruder had a significant effect on the cooking quality of the rice vermicelli extrudate.

Keywords: cooking loss, cooking quality, cooking yield, extruded rice vermicelli, twin-screw extruder, water absorption index

Procedia PDF Downloads 83