Search results for: feature combination

Authors: Vahid Hosseinzadeh

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Salafism is a movement of thought-religion that was born into Sunni Islam and Hanbali sect. However, many groups and different attitudes call themselves Salafis, but they all have common characteristics, the main of which is radical and retrograde interpretation of Islamic sources. Taqi Ad-Din Ahmad ibn Taymiyyah in the Muslim world was the first thinker who established these thoughts. The authors of this article initially tried to express the meaning of Salafism and its appellation in order to focus on the beliefs and thoughts of Ibn Taymiyyah. In this way, it was tried to extract the intellectual foundations of Ibn Taymiyya from the literature and scientific works of his own using a descriptive-analytical method. Extreme focus on the appearance of Quranic phrases and opposition to any new thing that did not exist in Qur'an, Sunnah and the first 3 centuries of Islam, are among the central feature of his thoughts.

Keywords: Salafism, Ibn Taymiyyah, radical literalism, monotheism, polytheism, takfir

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Authors: Yang Cao

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Analyzing the oral production of Chinese-speaking learners of English as a second language (L2), we can find a large variety of verb inflections – Why does it seem so hard for them to use consistent correct past morphologies in obligatory past contexts? Failed Functional Features Hypothesis (FFFH) attributes the rather non-target-like performance to the absence of [±past] feature in their L1 Chinese, arguing that for post puberty learners, new features in L2 are no more accessible. By contrast, Missing Surface Inflection Hypothesis (MSIH) tends to believe that all features are actually acquirable for late L2 learners, while due to the mapping difficulties from features to forms, it is hard for them to realize the consistent past morphologies on the surface. However, most of the studies are limited to the verb morphologies in finite clauses and few studies have ever attempted to figure out these learners’ performance in non-finite clauses. Additionally, it has been discussed that Chinese learners may be able to tell the finite/infinite distinction (i.e. the [±finite] feature might be selected in Chinese, even though the existence of [±past] is denied). Therefore, adopting a self-paced reading task (SPR), the current study aims to analyze the processing patterns of Chinese-speaking learners of L2 Russian, in order to find out if they are sensitive to misuse of tense morphologies in both finite and non-finite clauses and whether they are sensitive to the finite/infinite distinction presented in Russian. The study targets L2 Russian due to its systematic morphologies in both present and past tenses. A native Russian group, as well as a group of English-speaking learners of Russian, whose L1 has definitely selected both [±finite] and [±past] features, will also be involved. By comparing and contrasting performance of the three language groups, the study is going to further examine and discuss the two theories, FFFH and MSIH. Preliminary hypotheses are: a) Russian native speakers are expected to spend longer time reading the verb forms which violate the grammar; b) it is expected that Chinese participants are, at least, sensitive to the misuse of inflected verbs in non-finite clauses, although no sensitivity to the misuse of infinitives in finite clauses might be found. Therefore, an interaction of finite and grammaticality is expected to be found, which indicate that these learners are able to tell the finite/infinite distinction; and c) having selected [±finite] and [±past], English-speaking learners of Russian are expected to behave target-likely, supporting L1 transfer.

Keywords: features, finite clauses, morphosyntax, non-finite clauses, past morphologies, present morphologies, Second Language Acquisition, self-paced reading task, verb inflections

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Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Muhammad Suhail Ibrahim, Ahmad Mujtaba

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Background: The accuracy of the most frequently used tests for diagnosing Helicobacter pylori is always under consideration in clinical settings. A reliable diagnosis is crucial to confirm the success of therapy. Objective: The aim of this research was to study the isolation frequency of H. pylori from patients compatible with gastritis or gastric ulcer and to compare some feasible non-invasive and invasive methods for the diagnosis of infection. Materials and Methods: Ninety-six gastric biopsy and blood samples were obtained with various gastroduodenal symptoms after obtaining informed consent. The biopsies were analyzed and compared using the culture, microscopic examination, histopathology, Rapid urease RUT), serology, biochemical, antibiotic susceptibility test and molecular method. Results: A number of 40 (41.67%) were considered H. pylori positive in both histopathology and RUT. On the other hand, 46 patients were positive against anti IgA and IgG by ELISA. Eighteen biopsies were positive according to the culture test. This was further confirmed by endoscopic examination, urease, catalase and oxidase tests. A high percentage of resistance to polymyxin B, amoxicillin, and kanamycin was observed (100, 88.89, and 77.78%, respectively). A gene (Cag A) was also detected by using molecular technique which appeared positive in 16 patients. The sensitivity/specificity (%) of diagnostic method was 95/77 for histology, 100/83.5 for rapid urease, 85.7/90 for gram staining, 100/66.6 for IgG serology, 100/79.5 for IgA serology, 100/75.0 for PCR, 100/79.04 for combination of RUT and IgG serology and 100/92.4 for combination of RUT, gram staining and IgG serology. Conclusion: In view of the result obtained, PCR appeared to be the most reliable test. However, higher sensitivity and specificity were also recorded for other tests. So, for more accurate results, it is advisable not to rely solely on a single method for detection.

Keywords: helicobacter pylori, isolation, detection, culture, urease, polymerase chain reaction, antibiotic susceptibility test, dyspeptic patients

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Authors: Taliah Foudah, Sana Masri, Jana Al Ghamdi, Rimaz Alzaaqi

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This research project explores the creative works of the app Metui, which allows consumers to edit their photos and use the new and popular AI feature, which turns any photo into a cartoon-like animated image with beautified enhancements. Studying this AI app demonstrates the significance of the ability in which AI can develop intricate designs which verily replicate the human mind. Our goal was to investigate the Metui app by asking our audience certain questions about its functionality and their personal feelings about its credibility as well as their beliefs as to how this app will add to the future of the AI generation, both positively and negatively. Their responses were further explored by analyzing the questions and responses thoroughly and calculating the results through pie charts. Overall, it was concluded that the Metui app is a powerful step forward for AI by replicating the intelligence of humans and its creativity to either benefit society or do the opposite.

Keywords: AI Art, Meitu, application, photo editing

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Authors: Adeleye Oluwagbemmiga, Obuotor Tolulope, Dosumu Adebisi, Opowoye I., Olasoju M., Kolawole Amos, Egbeyale Lawrence

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Gut Microbiota plays a vital role in animal health and welfare. This study investigated the effect of naringin and hesperidin administration on broiler birds. A total of 80 day – old broiler chicks were randomly divided into eight groups, with ten birds per group. Four groups were not inoculated but administered coccidiostat (1A), hesperidin alone (2A), naringin alone (3A) and a combination of naringin and hesperidin (4A) from day eight (8) to day fourteen (14) while four other groups (5A – 8A) were inoculated with 2 x 10⁴ oocysts per 0.5ml of Eimeria tenella on the 16th and 19th day of age after they were administered conventional antibiotics and coccidiostat, naringin (50mg/body weight), hesperidin (50mg/body weight) and a combination from day 8 - 14. McMaster counting technique was used to count the oocysts, while pour plate technique was used to determine the bacterial load. The results showed a significant increase in their performance with an average weight ranging from 1.55kg – 2.00kg, microbial load also improved with colony count values from 3.5 x 104 - 4.5 x 10⁴ CFU/ml. The study also found that the inclusion of naringin and hesperidin in the diets of broiler birds inoculated with coccidia oocysts significantly reduced the fecal oocyst counts, with the lowest count in combined treatment (8A) (10%) and indicating a lower degree of coccidiosis infection in the treated groups whereas control group (5A) had the highest oocyst count (35%). Mortality and Morbidity rate was 0% as none of the bird showed signs and symptoms. The reduction in oocyst counts could help to strengthen the immune system of broiler birds and limit the severity of coccidiosis infection, which could be an effective strategy for improving performance, immune function and mitigating the impact of coccidiosis infection in broiler birds.

Keywords: gut colonization, naringin, hesperidin, eimeria tenella, broilers

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Mohhamed Yassine Baroudi, Abdelkrim Benammar, Fethi Tarik Bendimerad

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This paper proposes software architecture for dynamical service adaptation. The services are constituted by reusable software components. The adaptation’s goal is to optimize the service function of their execution context. For a first step, the context will take into account just the user needs but other elements will be added. A particular feature in our proposition is the profiles that are used not only to describe the context’s elements but also the components itself. An adapter analyzes the compatibility between all these profiles and detects the points where the profiles are not compatibles. The same Adapter search and apply the possible adaptation solutions: component customization, insertion, extraction or replacement.

Keywords: adaptative service, software component, service, dynamic adaptation

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Authors: Aibek Kukpayev, Dhawal Shah

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Combustion of sour fuels containing high amount of sulfur leads to the formation of sulfur oxides, which adversely harm the environment and has a negative impact on human health. Considering this, several legislations have been imposed to bring down the sulfur content in fuel to less than 10 ppm. In recent years, novel deep eutectic solvents (DESs) have been developed to achieve deep desulfurization, particularly to extract thiophenic compounds from liquid fuels. These novel DESs, considered as analogous to ionic liquids are green, eco-friendly, inexpensive, and sustainable. We herein, using molecular dynamic simulation, analyze the interactions of metal-based DESs with model oil consisting of thiophenic compounds. The DES used consists of polyethylene glycol (PEG-200) as a hydrogen bond donor, choline chloride (ChCl) or tetrabutyl ammonium chloride (TBAC) as a hydrogen bond acceptor, and cobalt chloride (CoCl₂) as metal salt. In particular, the combination of ChCl: PEG-200:CoCl₂ at a ratio 1:2:1 and the combination of TBAC:PEG-200:CoCl₂ at a ratio 1:2:0.25 were simulated, separately, with model oil consisting of octane and thiophenes at 25ᵒC and 1 bar. The results of molecular dynamics simulations were analyzed in terms of interaction energies between different components. The simulations revealed a stronger interaction between DESs/thiophenes as compared with octane/thiophenes, suggestive of an efficient desulfurization process. In addition, our analysis suggests that the choice of hydrogen bond acceptor strongly influences the efficiency of the desulfurization process. Taken together, the results also show the importance of the metal ion, although present in small amount, in the process, and the role of the polymer in desulfurization of the model fuel.

Keywords: deep eutectic solvents, desulfurization, molecular dynamics simulations, thiophenes

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Authors: Nino Tsamalaidze

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Cold plasma is an ionized neutral gas with a temperature of 30-40 degrees, but the impact of HP includes not only gas, but also active molecules, charged particles, heat and UV radiation of low power The main goal of the technology we describe is to launch the natural function of skin regeneration and improve the metabolism inside, which leads to a huge effect of rejuvenation. In particular: eliminate fine mimic wrinkles; get rid of wrinkles around the mouth (purse-string wrinkles); reduce the overhang of the upper eyelid; eliminate bags under the eyes; provide a lifting effect on the oval of the face; reduce stretch marks; shrink pores; even out the skin, reduce the appearance of acne, scars; remove pigmentation. A clear indication of the major findings of the study is based on the current patients practice. The method is to use combination of cold plasma and liquid threats. The advantage of cold plasma is undoubtedly its efficiency, the result of its implementation can be compared with the result of a surgical facelift, despite the fact that the procedure is non-invasive and the risks are minimized. Another advantage is that the technique can be applied on the most sensitive skin of the face - these are the eyelids and the space around the eyes. Cold plasma is one of the few techniques that eliminates bags under the eyes and overhanging eyelids, while not violating the integrity of the tissues. In addition to rejuvenation and lifting effect, among the benefits of cold plasma is also getting rid of scars, kuperoze, stretch marks and other skin defects, plasma allows to get rid of acne, seborrhea, skin fungus and even heals ulcers. The cold plasma method makes it possible to achieve a result similar to blepharoplasty. Carried out on the skin of the eyelids, the procedure allows non-surgical correction of the eyelid line in 3-4 sessions. One of the undoubted advantages of this method is a short rehabilitation and rapid healing of the skin.

Keywords: wrinkles, telangiectasia, pigmentation, pore closing

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Authors: Anusha Atmakuri, R. D. Tyagi, Patrick Drogui

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Landfilling is the most familiar and easy way to dispose solid waste. Landfill is generally received via wastes from municipal near to a landfill. The waste collected is from commercial, industrial, and residential areas and many more. Landfill leachate (LFL) is formed when rainwater passes through the waste placed in landfills and consists of several dissolved organic materials, for instance, aquatic humic substances (AHS), volatile fatty acids (VFAs), heavy metals, inorganic macro components, and xenobiotic organic matters, highly toxic to the environment. These components of LFL put a load on it, hence it necessitates the treatment of LFL prior to its discharge into the environment. Various methods have been used to treat LFL over the years, such as physical, chemical, biological, physicochemical, electrical, and advanced oxidation methods. This study focuses on the combination of biological and electrochemical methods- extracellular polymeric substances and electrocoagulation(EC). The coupling of electro-coagulation process with extracellular polymeric substances (EPS) (as flocculant) as pre and\or post treatment strategy provides efficient and economical process for the decontamination of landfill leachate contaminated with suspended matter, metals (e.g., Fe, Mn) and ammonical nitrogen. Electro-coagulation and EPS mediated coagulation approach could be an economically viable for the treatment of landfill leachate, along with possessing several other advantages over several other methods. This study utilised waste substrates such as activated sludge, crude glycerol and waste cooking oil for the production of EPS using fermentation technology. A comparison of different scenarios for the treatment of landfill leachate is presented- such as using EPS alone as bioflocculant, EPS and EC with EPS being the 1st stage, and EPS and EC with EC being the 1st stage. The work establishes the use of crude EPS as a bioflocculant for the treatment of landfill leachate and wastewater from a site near a landfill, along with EC being successful in removal of some major pollutants such as COD, turbidity, total suspended solids. A combination of these two methods is to be explored more for the complete removal of all pollutants from landfill leachate.

Keywords: landfill leachate, extracellular polymeric substances, electrocoagulation, bioflocculant.

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Authors: S. D. El Wakil, M. Pladsen

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Fiber reinforced polymeric (FRP) composites are finding wide-spread industrial applications because of their exceptionally high specific strength and specific modulus of elasticity. Nevertheless, it is very seldom to get ready-for-use components or products made of FRP composites. Secondary processing by machining, particularly drilling, is almost always required to make holes for fastening components together to produce assemblies. That creates problems since the FRP composites are neither homogeneous nor isotropic. Some of the problems that are encountered include the subsequent damage in the region around the drilled hole and the drilling – induced delamination of the layer of ply, that occurs both at the entrance and the exit planes of the work piece. Evidently, the functionality of the work piece would be detrimentally affected. The current work was carried out with the aim of eliminating or at least minimizing the work piece damage associated with drilling of FPR composites. Each test specimen involves a woven reinforced graphite fiber/epoxy composite having a thickness of 12.5 mm (0.5 inch). A large number of test specimens were subjected to drilling operations with different combinations of feed rates and cutting speeds. The drilling induced damage was taken as the absolute value of the difference between the drilled hole diameter and the nominal one taken as a percentage of the nominal diameter. The later was determined for each combination of feed rate and cutting speed, and a matrix comprising those values was established, where the columns indicate varying feed rate while and rows indicate varying cutting speeds. Next, the analysis of variance (ANOVA) approach was employed using Minitab software, in order to obtain the combination that would improve the drilling induced damage. Experimental results show that low feed rates coupled with low cutting speeds yielded the best results.

Keywords: drilling of composites, dimensional accuracy of holes drilled in composites, delamination and charring, graphite-epoxy composites

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Authors: Mohamed Shafi Mahboob Ali

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Male breast cancer (MBC) is a rare entity with overall cases reported less than 1%. However, the incidence of MBC is regularly rising every year. Due to the lack of data on MBC, diagnosis and treatment are tailored to female breast cancer. MBC risk increases with age and is usually diagnosed ten years late as the disease progression is slow compared to female breast cancer (FBC). The most common feature of MBC is an intra-ductal variant, and often, upon diagnosis, the stage of the disease is already advanced. The Prognosis of MBC is often flawed, but new treatment modalities are emerging with the current knowledge and advancement. We presented a series of male breast cancer in our center, highlighting the clinicopathological, radiological and treatment options.

Keywords: male, breast, cancer, clinicopathology, ultrasound, CT scan

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Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: Mounir Zili

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We will introduce a new extension of the Brownian motion, that could serve to get a good model of many natural phenomena. It is a linear combination of a finite number of sub-fractional Brownian motions; that is why we will call it the mixed sub-fractional Brownian motion. We will present some basic properties of this process. Among others, we will check that our process is non-Markovian and that it has non-stationary increments. We will also give the conditions under which it is a semimartingale. Finally, the main features of its sample paths will be specified.

Keywords: mixed Gaussian processes, Sub-fractional Brownian motion, sample paths

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Authors: Frieda Eivazi, Nikita L. Mullings

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Soils are recipient for surfactants in herbicide formulations. Surfactants entering the soil environment can possibly disrupt different chemical, physical and biological interactions. Therefore, it is critical that we understand the fate, behavior and transport of surfactants upon entering the soil. A comprehensive study was conducted to examine effect of surfactants on nutrient uptake, microbial community, and enzyme activity. The research was conducted in the greenhouse growing corn (Zea mays) as a test plant in a factorial experiment (three surfactants at two different rates with control, and three herbicides) organized as randomized blocked design. Surfactants evaluated were Activator 90, Agri-Dex, and Thrust; herbicides were glyphosate, atrazine, and bentazon. Treatments examined were surfactant only, herbicide only, and surfactant + herbicide combinations. Corn was planted in fertilized soils (silt loam and silty clay) with moisture content maintained at the field capacity for optimum growth. This paper will report results of above mentioned treatments on acid phosphatase, beta-glucosidase, arylsulfatase, beta-glucosaminidase, and dehydrogenase activities. In general, there were variations in the enzyme activities with some inhibition and some being enhanced by the treatments. Activator 90 appeared to have the highest inhibitory effect on enzymatic activities. Atrazine application significantly decreased the activities of acid phosphatase, beta-glucosidase, and dehydrogenase in both soils; however, combination of Atrazine + Agridex increased the acid phosphatase activity while significantly inhibiting the other enzyme activities in soils. It was concluded that long-term field studies are needed to validate changes in nutrient uptake, microbial community and enzyme activities due to surfactant-herbicide combination effects.

Keywords: herbicides, nutrient cycling, soil enzymes, surfactant

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Authors: Mahdi Shaghaghi, Amir Ghaebi, Fariba Ahmadi

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Purpose: The main purpose of the present research is to analyze the knowledge creation environment at a Iranian University (Alzahra University) as a typical University in Iran, using a combination of the i-System and Ba models. This study is necessary for understanding the determinants of knowledge creation at Alzahra University as a typical University in Iran. Methodology: To carry out the present research, which is an applied study in terms of purpose, a descriptive survey method was used. In this study, a combination of the i-System and Ba models has been used to analyze the knowledge creation environment at Alzahra University. i-System consists of 5 constructs including intervention (input), intelligence (process), involvement (process), imagination (process), and integration (output). The Ba environment has three pillars, namely the infrastructure, the agent, and the information. The integration of these two models resulted in 11 constructs which were as follows: intervention (input), infrastructure-intelligence, agent-intelligence, information-intelligence (process); infrastructure-involvement, agent-involvement, information-involvement (process); infrastructure-imagination, agent-imagination, information-imagination (process); and integration (output). These 11 constructs were incorporated into a 52-statement questionnaire and the validity and reliability of the questionnaire were examined and confirmed. The statistical population included the faculty members of Alzahra University (344 people). A total of 181 participants were selected through the stratified random sampling technique. The descriptive statistics, binomial test, regression analysis, and structural equation modeling (SEM) methods were also utilized to analyze the data. Findings: The research findings indicated that among the 11 research constructs, the levels of intervention, information-intelligence, infrastructure-involvement, and agent-imagination constructs were average and not acceptable. The levels of infrastructure-intelligence and information-imagination constructs ranged from average to low. The levels of agent-intelligence and information-involvement constructs were also completely average. The level of infrastructure-imagination construct was average to high and thus was considered acceptable. The levels of agent-involvement and integration constructs were above average and were in a highly acceptable condition. Furthermore, the regression analysis results indicated that only two constructs, viz. the information-imagination and agent-involvement constructs, positively and significantly correlate with the integration construct. The results of the structural equation modeling also revealed that the intervention, intelligence, and involvement constructs are related to the integration construct with the complete mediation of imagination. Discussion and conclusion: The present research suggests that knowledge creation at Alzahra University relatively complies with the combination of the i-System and Ba models. Unlike this model, the intervention, intelligence, and involvement constructs are not directly related to the integration construct and this seems to have three implications: 1) the information sources are not frequently used to assess and identify the research biases; 2) problem finding is probably of less concern at the end of studies and at the time of assessment and validation; 3) the involvement of others has a smaller role in the summarization, assessment, and validation of the research.

Keywords: i-System, Ba model , knowledge creation , knowledge management, knowledge creation environment, Iranian Universities

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini, Omid Seyed Esmaeili, Rouzbeh Kezemi, Noushin Mehrbod, Nazanin Vahed, Tahereh Hajiahmad, Noureddin Nakhostin Ansari

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Background: Stroke is a disabling neurological disease. Rehabilitative therapies are important treatment methods. This clinical trial was done to compare the effects of VR beside conventional rehabilitation versus conventional rehabilitation alone on spasticity and motor function in stroke patients. Materials and Methods: In this open-label randomized controlled clinical trial, 40 consecutive patients with stable first-ever ischemic stroke in the past three to 12 months that were referred to a rehabilitation clinic in Tehran, Iran, in 2020 were enrolled. After signing the informed written consent form, subjects were randomly assigned by block randomization of five in each block as cases with 1:1 into two groups of 20 cases; conventional plus VR therapy group: 45-minute conventional therapy session plus 15-minute VR therapy, and conventional group: 60-minute conventional therapy session. VR rehabilitation is designed and developed with different stages. Outcomes were modified Ashworth scale, recovery stage score for motor function, range of motion (ROM) of shoulder abduction/wrist extension, and patients’ satisfaction rate. Data were compared after study termination. Results: The satisfaction rate among the patients was significantly better in the combination group (P=0.003). Only wrist extension was varied between groups and was better in the combination group. The variables generally had a statistically significant difference (P < 0.05). Conclusion: Virtual reality plus conventional rehabilitation therapy is superior versus conventional rehabilitation alone on the wrist and elbow spasticity and motor function in patients with stroke.

Keywords: stroke, virtual therapy, rehabilitation, treatment

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Authors: L. Freeman, D. Bax, V. K. Sapong

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Community-based, preventative approaches to violent extremism may be effective and yet remain an underutilised method. In a realm where security approaches dominate, with the focus on countering violence extremism and combatting radicalisation, community resilience programming remains sparse. This paper will present a survey tool that aims to measure the risk and protective factors that can lead to violent extremism in Mozambique and Tanzania. Conducted in four districts in the Cabo Delgado region of Mozambique and one district in Pwani, Tanzania, the survey uses a combination of BRAVE-14, Afrocentric and context-specific questions in order to more fully understand community resilience opportunities and challenges in preventing and countering violent extremism. Developed in Australia and Canada to measure radicalisation risks in individuals and communities, BRAVE-14 is a tool not yet applied in the African continent. Given the emerging threat of Islamic extremism in Northern Mozambique and Eastern Tanzania, which both experience a combination of socio-political exclusion, resource marginalisation and religious/ideological motivations, the development of the survey is timely and fills a much-needed information gap in these regions. Not only have these Islamist groups succeeded in tapping into the grievances of communities by radicalising and recruiting individuals, but their presence in these regions has been characterised by extreme forms of violence, leaving isolated communities vulnerable to attack. The expected result of these findings will facilitate the contextualisation and comparison of the protective and risk factors that inhibit or promote the radicalisation of the youth in these communities. In identifying sources of resilience and vulnerability, this study emphasises the implementation of context-specific intervention programming and provides a strong research tool for understanding youth and community resilience to violent extremism.

Keywords: community resilience, Mozambique, preventing violent extremism, radicalisation, Tanzania

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Authors: Bechir Hbibi, Lamine Mili

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Understanding the condition of comatose patients can be difficult, but it is crucial to their optimal treatment. Consequently, numerous scoring systems have been developed around the world to categorize patient states based on physiological assessments. Although validated and widely adopted by medical communities, these scores still present numerous limitations and obstacles. Even with the addition of additional tests and extensions, these scoring systems have not been able to overcome certain limitations, and it appears unlikely that they will be able to do so in the future. On the other hand, physiological tests are not the only way to extract ideas about comatose patients. EEG signal analysis has helped extensively to understand the human brain and human consciousness and has been used by researchers in the classification of different levels of disease. The use of EEG in the ICU has become an urgent matter in several cases and has been recommended by medical organizations. In this field, the EEG is used to investigate epilepsy, dementia, brain injuries, and many other neurological disorders. It has recently also been used to detect pain activity in some regions of the brain, for the detection of stress levels, and to evaluate sleep quality. In our recent findings, our aim was to use multifractal analysis, a very successful method of handling multifractal signals and feature extraction, to establish a state of awareness scale for comatose patients based on their electrical brain activity. The results show that this score could be instantaneous and could overcome many limitations with which the physiological scales stock. On the contrary, multifractal analysis stands out as a highly effective tool for characterizing non-stationary and self-similar signals. It demonstrates strong performance in extracting the properties of fractal and multifractal data, including signals and images. As such, we leverage this method, along with other features derived from EEG signal recordings from comatose patients, to develop a scale. This scale aims to accurately depict the vigilance state of patients in intensive care units and to address many of the limitations inherent in physiological scales such as the Glasgow Coma Scale (GCS) and the FOUR score. The results of applying version V0 of this approach to 30 patients with known GCS showed that the EEG-based score similarly describes the states of vigilance but distinguishes between the states of 8 sedated patients where the GCS could not be applied. Therefore, our approach could show promising results with patients with disabilities, injected with painkillers, and other categories where physiological scores could not be applied.

Keywords: coma, vigilance state, EEG, multifractal analysis, feature extraction

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Authors: Seyed Nima Tayarani Bathaie

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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: face detection algorithm, Haar features, security of ATM

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Authors: Tamer M. Shehata

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Objective: Currently, mucoadhesive microparticles acquired a high interest in both research and pharmaceutical technology fields. Recently, BÜCHI lunched its latest fourth generation nano spray dryer B-90 used for nanoparticle production. B-90 offers an elegant technology combined particle engineering and drying in one step. In our laboratory, we successfully developed a new formulation for metformin hydrochloride, mucoadhesive microparticles utilizing B-90 technology for treatment of type 2-diabetis. Method: Gelatin or sodium alginate, natural occurring polymers with mucoadhesive properties, solely or in combination was used in our formulation trials. Preformulation studies (atomization head mesh size, flow rate, head temperature, polymer solution viscosity and surface tension) and postformulation characters (particle size, flowability, surface scan and dissolution profile) were evaluated. Finally, hypoglycemic effect of the selected formula was evaluated in streptozotocin-induced diabetic rats. Spray head with 7 µm hole, flow rate of 3.5 mL/min and head temperature 120 ºC were selected. Polymer viscosity was less than 11.5 cP with surface tension less than 70.1 dyne/cm. Result: Discrete, non aggregated particles and free flowing powders with particle size was less than 2000 nm were obtained. Gelatin and sodium alginate combination in ratio 1:3 were successfully sustained the in vitro release profile of the drug. Hypoglycemic evaluation of the previous formula, showed a significant reduction of blood glucose level over 24 h. Conclusion: B-90 technology can open a new era of , mucoadhesive microparticles preparation offering convenient dosage form that can enhance compliance of type 2 diabetic patients.

Keywords: mucoadhesive, microparticles, technology, diabetis

Procedia PDF Downloads 285

Authors: F. Rarbi, D. Dzahini, W. Uhring

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In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm². The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register

Procedia PDF Downloads 410

Authors: Nayira A. Abd Elbaky, Amal J. Fatani, Hazar Yaqub, Nouf M. Al-Rasheed, Naglaa El-Orabi, Mai Osman

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The present work is aimed to evaluate the protective effect of N-acetyl cystiene (NAC), coenzyme Q10 (CoQ10), and their combination against carbon tetrachloride (CCl4)-induced cardiotoxicity in rats. CCl4 treatment significantly elevated the levels of cardiac oxidative stress bio markers including nitric oxide (NO) and malondialdehyde (MDA). A concomitant decrease in the level of reduced glutathione and the activity of membrane bound enzyme, calcium-adenosine triphosphatase were observed in the hearts of rats exposed to CCl4 compared to respective values in normal group. Quantitative analysis of myocardial energy metabolism revealed a significant decrease in the glucose content coupled with depletion in the activities of myocardial glycolytic enzymes as hexokinase (HK), phosphofructokinase (PFK) and lactate dehydrogenase (LDH) after CCl4 treatment. In addition, a significant elevation in myocardial hydroxyproline level was observed in CCl4 intoxicated rats indicating interstitial collagen accumulation. Pretreatment with either NAC, CoQ10 or their combination successively alleviated the alterations in myocardial oxidative stress and antioxidant markers, as well as effectively up-regulated the decrease in cardiac energetic biomarkers in CCl4 intoxicated rats. Moreover, these antioxidants markedly reduced myocardial hydroxyproline level versus that of CCl4-treated animals. In conclusion, the present results illustrated that the prophylactic use of the current antioxidant resulted in a remarkable cardioprotective effect against CCl4 induced myocardial damage, which suggest that they may candidates as prophylactic agents against different cardio-toxins.

Keywords: carbon tetrachloride, lipid peroxidation, antioxidant, energy metabolism, hydroxyproline

Procedia PDF Downloads 392

Authors: S. F. Wong, W. I. Ho, B. Lin, Q. Huang

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ERP has been used in many enterprises for management, the accuracy of the production forecasting module is vital to the decision making of the enterprise, and the profit is affected directly. Therefore, enhancing the accuracy of the production forecasting module can also increase the efficiency and profitability. To deal with a lot of data, a suitable, reliable and accurate statistics model is necessary. LSSVM and Grey System are two main models to be studied in this paper, and a case study is used to demonstrate how the combination model is effective to the result of forecasting.

Keywords: ERP, grey system, LSSVM, production forecasting

Procedia PDF Downloads 453

Authors: Ying-Hsiang Ho, Hsiao-Tseng Lin

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Mudan Township is a remote mountainous area in Taiwan. In recent years, due to the migration of the population, inconvenient transportation, digital divide, and low production, agricultural products marketing have become a major issue. This research aims to develop the marketing strategy suitable for the agricultural products of the rural areas. The main objective of this work is to conduct in-depth interviews with scholars and experts in the marketing field, combined with the marketing 4P combination, to analyze and summarize the possible marketing strategies for agricultural products for remote districts. The interviews consist of seven experts from industry who have practical experience in producing, marketing, and selling agricultural products and three professors that have experience in teaching marketing management. The in-depth interviews are conducted for about an hour using a pre-drafted interview outline. The results of the interviews are summarized by semantic analysis and presented in a marketing 4P combination. The results indicate that in terms of products, high-quality products with original characteristics can be added through the implementation of production history, organic certification, and cultural packaging. In the place part, we found that the use of emerging communities, the emphasis on cross-industry alliances, the improvement of information application capabilities of rural households, production and marketing group, and contractual farming system are the development priorities. In terms of promotion, it should be an emphasis on the management of internet social media and word-of-mouth marketing. Mudan Township may consider promoting agricultural products through special festivals such as farmer's market, wild ginger flower season and hot spring season. This research also proposes relevant recommendations for the government's public sector and related industry reference for the promotion of agricultural products for remote area.

Keywords: marketing strategy, remote districts, agricultural products, in-depth interviews

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Authors: Jonathan Ham, Christopher Koch

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There are consistently observed associations between certain odors and colors, and there is an association between the ability to imagine vivid visual objects and imagine vivid odors. However, little has been done to investigate how the associations between odors and visual information effect visual processes. This study seeks to understand the relationship between odor imaging, color associations, and visual attention by utilizing a Stroop-task based on common odor-color associations. This Stroop-task was designed using three fruits with distinct odors that are associated with the color of the fruit: lime with green, strawberry with red, and lemon with yellow. Each possible word-color combination was presented in the experimental trials. When the word matched the associated color (lime written in green) it was considered congruent; if it did not, it was considered incongruent (lime written in red or yellow). In experiment I (n = 34) participants were asked to both imagine the odor of the fruit on the screen and identify which fruit it was, and each word-color combination was presented 20 times (a total of 180 trials, with 60 congruent and 120 incongruent instances). Response time and error rate of the participant responses were recorded. There was no significant difference in either measure between the congruent and incongruent trials. In experiment II participants (n = 18) followed the identical procedure as in the previous experiment with the addition of an odorant in the room. The odorant (orange) was not the fruit or color used in the experimental trials. With a fruit-based odorant in the room, the response times (measured in milliseconds) between congruent and incongruent trials were significantly different, with incongruent trials (M = 755.919, SD = 239.854) having significantly longer response times than congruent trials (M = 690.626, SD = 198.822), t (1, 17) = 4.154, p < 0.01. This suggests that odor imagery does affect visual attention to colors, and the ability to inhibit odor-color associations; however, odor imagery is difficult and appears to be facilitated in the presence of a related odorant.

Keywords: odor-color associations, odor imagery, visual attention, inhibition

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

Procedia PDF Downloads 142