Search results for: average small signal model

Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Sukritta Larsen, Kevin Wongleedee

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The purposes of this research were to study tourists’ destination loyalty from the perspective of international tourists in Bangkok and to study the level of interest to revisit Bangkok in the near future. A probability random sampling of 200 international tourists was utilized. Half of the sample group was male and the other half was female. A Likert-five-scale questionnaire was designed to collect the data and small in-depth interviews were also used to obtain their opinions. The findings revealed that the majority of respondents had a medium level of loyalty. When examined in detail, the destination loyalty indicators can be ranked according to the mean average from high to low as follows: to recommend the visit, to say positive things, to revisit in the next three years, to refer the information, and to plan to visit regularly. Finally, the findings from the in-depth interviews with small group of international tourists revealed that the major obstacles that prevented many international tourists who may interested in revisiting Thailand included traffic congestions, high crime rate, and political instability.

Keywords: destination loyalty, international tourists, revisit, Bangkok

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Authors: Ho Jeong Jin, Chang Won Seo, Choon Sik Cho, Bong Yong Choi, Kwang Kyun Na, Sang Rok Lee

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In this paper, a radar signal processing technique using the LFM-FSK (Linear Frequency Modulation-Frequency Shift Keying) is proposed for reducing the false alarm rate based on the compressive sensing. The LFM-FSK method combines FMCW (Frequency Modulation Continuous Wave) signal with FSK (Frequency Shift Keying). This shows an advantage which can suppress the ghost phenomenon without the complicated CFAR (Constant False Alarm Rate) algorithm. Moreover, the parametric sparse algorithm applying the compressive sensing that restores signals efficiently with respect to the incomplete data samples is also integrated, leading to reducing the burden of ADC in the receiver of radars. 24 GHz FMCW signal is applied and tested in the real environment with FSK modulated data for verifying the proposed algorithm along with the compressive sensing.

Keywords: compressive sensing, LFM-FSK radar, radar signal processing, sparse algorithm

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Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: agro-industry, small medium enterprises, empowerment, design thinking, AHP, business model canvas, social business

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Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Joel Bonales, Venecia Solorzano, Carlos Garcia

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A great percentage of the wastewater generated in developing countries don’t receive any treatment, which leads to numerous environmental impacts. In response to this, a paradigm change in the current wastewater treatment model based on large scale plants towards a small and medium scale based model has been proposed. Nevertheless, small scale wastewater treatment (SS-WTTP) with novel technologies such as anaerobic digesters, as well as the utilization of derivative co-products such as biogas, still presents diverse environmental impacts which must be assessed. This study consisted in a Life Cycle Assessment (LCA) performed to a SS-WWTP which treats wastewater from a small commercial block in the city of Morelia, Mexico. The treatment performed in the SS-WWTP consists in anaerobic and aerobic digesters with a daily capacity of 5,040 L. Two different scenarios were analyzed: the current plant conditions and a hypothetical energy use of biogas obtained in situ. Furthermore, two different allocation criteria were applied: full impact allocation to the system’s main product (treated water) and substitution credits for replacing Mexican grid electricity (biogas) and clean water pumping (treated water). The results showed that the analyzed plant had bigger impacts than what has been reported in the bibliography in the basis of wastewater volume treated, which may imply that this plant is currently operating inefficiently. The evaluated impacts appeared to be focused in the aerobic digestion and electric generation phases due to the plant’s particular configuration. Additional findings prove that the allocation criteria applied is crucial for the interpretation of impacts and that that the energy use of the biogas obtained in this plant can help mitigate associated climate change impacts. It is concluded that SS-WTTP is a environmentally sound alternative for wastewater treatment from a systemic perspective. However, this type of studies must be careful in the selection of the allocation criteria and replaced products, since these factors have a great influence in the results of the assessment.

Keywords: biogas, life cycle assessment, small scale treatment, wastewater treatment

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Authors: E. Rak

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The aim of the paper is to identify some of the specific characteristics of employee development, as observed in the practice of small enterprises in Poland. Results suggest that a sizeable percentage of employers are not interested in improving the development of their employee base. This aspect is often perceived as insignificant. In addition, many employers have no theoretical or practical knowledge of employee development methods. Lack of sufficient financial support is reported as third on the list of the most important barriers to employee development. Employees, on the other hand, typically offload the responsibility of initiating this type of activities onto the employer. Employee development plans are typically flexible and accommodating. The original value offered by this research comes in the form of a detailed characteristics of employee development in small enterprises, accompanied by identification of specificity of human resource development in Polish companies.

Keywords: employee development, human resources development, small enterprises, trainings

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Authors: Mohamed H. El-Sheikh, Hoda F. Zahran

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Olive tree (Olea europaea L.) is considered as a Mediterranean tree which belongs to genus Olea that may comprise about 35 species. In fact, the crop requires mild to cool winters with a chilling accumulation from November to February with average temperatures varying between two groups of accumulated chilling hours (h1) of less than 7.2 °C (C1) and other group (h2) of less than 10 °C (C2) for flower bud differentiation. This work aims at studying the impact of chilling accumulation hours on the fruit yield of olive trees in Borg El Arab City, Alexandria Governorate, Egypt as a case study. Trees were aged around 7 years in 2010 and were exposed to chilling accumulation hours of h1, which was average of 280 hours under C1, and average h2 was around 150 hours under C2 the resulted fruit yield was around 0.5 kg/tree. On the hand, trees were aged around 7 years at 2016 showed that when average of h1 was around 390 hours under C1 and average h2 was around 220 hours under C2 then fruit yield was around 10 kg/tree. Increasing of fruit yield proved chilling accumulation effect on olive trees.

Keywords: chilling accumulation, fruit yield, Olea europaea, olive

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Authors: Julianne Cai, Weili Xue, Yibin Wu

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Social media retailing (SMR) platforms have become popular nowadays. It is characterized by a creative combination of content creation and product selling, which differs from traditional e-tailing (TE) with product selling alone. Motivated by real-world practices like social media platforms “TikTok” and douyin.com, we endeavor to study if the SMR model performs better than the TE model in a monopoly setting. By building a stylized economic model, we find that the SMR model does not always outperform the TE model. Specifically, when the SMR platform collects less commission from the seller than the TE platform, the seller, consumers, and social welfare all benefit more from the SMR model. In contrast, the platform benefits more from the SMR model if and only if the creator’s social influence is high enough or the cost of content creation is small enough. For the incentive structure of the content rewards in the SMR model, we found that a strong incentive mechanism (e.g., the quadratic form) is more powerful than a weak one (e.g., the linear form). The previous one will encourage the creator to choose a much higher quality level of content creation and meanwhile allowing the platform, consumers, and social welfare to become better off. Counterintuitively, providing more generous content rewards is not always helpful for the creator (seller), and it may reduce her profit. Our findings will guide the platform to effectively design incentive mechanisms to boost the content creation and retailing in the SMR model and help the influencers efficiently create content, engage their followers (fans), and price their products sold on the SMR platform.

Keywords: content creation, creator economy, incentive strategy, platform retailing

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Liu Zhiyuan, Sun Zongdi

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In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested.

Keywords: Carbon trading price, carbon trading volume, BP neural network model, Shanghai City

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Authors: Hussien Ali, Mesfin Menza, Fitsum Hagos, Amare Haileslassie

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Climate change has perverse effects on agricultural productivity and natural resource base, negatively affecting the well-being of the households and communities. The government and NGOs promote climate smart agricultural (CSA) practices to help farmers adapt to and mitigate the negative effects of climate change. This study aims to identify widely available CSA practices and examine their impacts on food security and multi-dimensional poverty of rural farm households in the Central Rift Valley, Ethiopia. Using three-stage proportional to size sampling procedure, the study randomly selected 278 households from two kebeles from four districts each. A cross-sectional data of 2020/21 cropping season was collected using structured and pretested survey questionnaire. Food consumption score, dietary diversity score, food insecurity experience scale, and multidimensional poverty index were calculated to measure households’ welfare indicators. Multinomial endogenous switching regression model was used to assess average treatment effects of CSA on these outcome indicators on adopter and non-adopter households. The results indicate that the widely adopted CSA practices in the area are conservation agriculture, soil fertility management, crop diversification, and small-scale irrigation. Adopter households have, on average, statistically higher food consumption score, dietary diversity score and lower food insecurity access scale than non-adopters. Moreover, adopter households, on average, have lower deprivation score in multidimensional poverty compared to non-adopter households. Up scaling the adoption of CSA practices through the improvement of households’ implementation capacity and better information, technical advice, and innovative financing mechanisms is advised. Up scaling CSA practices can further promote achieving global goals such as SDG 1, SDG 2, and SDG 13 targets, aimed to end poverty and hunger and mitigate the adverse impacts of climate change, respectively.

Keywords: climate-smart agriculture, food security, multidimensional poverty, upscaling CSA, Ethiopia

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Authors: D. C. Soares, J. T. S. Santos, D. G. Costa, A. K. S. Abud, T. P. Nunes, A. V. D. Figueiredo, A. M. de Oliveira Junior

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Mangabeira (Hancornia speciosa Gomes), a native plant in Brazil, is found growing spontaneously in various regions of the country. The high perishability of tropical fruits such as mangaba, causes it to be necessary to use technologies that promote conservation, aiming to increase the shelf life of this fruit and add value. The objective of this study was to compare the mangabas lyophilisation curves behaviours with different sizes and maturation stages. The fruits were freeze-dried for a period of approximately 45 hours at lyophilizer Liotop brand, model L -108. It has been considered large the fruits between 38 and 58 mm diameter and small, between 23 and 28 mm diameter and the two states of maturation, intermediate and mature. Large size mangabas drying curves in both states of maturation were linear behaviour at all process, while the kinetic drying curves related to small fruits, independent of maturation state, had a typical behaviour of drying, with all the well-defined steps. With these results it was noted that the time of lyophilisation was suitable for small mangabas, a fact that did not happen with the larger one. This may indicate that the large mangabas require a longer time to freeze until reaches the equilibrium level, as it happens with the small fruits, going to have constant moisture at the end of the process. For both types of fruit were analysed water activity, acidity, protein, lipid, and vitamin C before and after the process.

Keywords: freeze dryer, mangaba, conservation, chemical characteristics

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Authors: Hyung-Jin Kim, Dae-Wan Kim, Moo-Yeon Lee

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The objective of this study is to experimentally investigate the heat transfer characteristics of 200 W class woofer speaker units with the input voice signals. The temperature and heat transfer characteristics of the 200 W class woofer speaker unit were experimentally tested with the several input voice signals such as 1500 Hz, 2500 Hz, and 5000 Hz respectively. From the experiments, it can be observed that the temperature of the woofer speaker unit including the voice-coil part increases with a decrease in input voice signals. Also, the temperature difference in measured points of the voice coil is increased with decrease of the input voice signals. In addition, the heat transfer characteristics of the woofer speaker in case of the input voice signal of 1500 Hz is 40% higher than that of the woofer speaker in case of the input voice signal of 5000 Hz at the measuring time of 200 seconds. It can be concluded from the experiments that initially the temperature of the voice signal increases rapidly with time, after a certain period of time it increases exponentially. Also during this time dependent temperature change, it can be observed that high voice signal is stable than low voice signal.

Keywords: heat transfer, temperature, voice coil, woofer speaker

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Authors: Haruo Okabayashi

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Human biological signals (pulse wave and brain wave, etc.) have a rhythm which shows fluctuations. This study investigates the relationship between fluctuations of biological signals which are shown by a finger plethysmogram (i.e., finger pulse wave) in conversation and anthropophobic tendency, and identifies whether the fluctuation could be an index of mental health. 32 college students participated in the experiment. The finger plethysmogram of each subject was measured in the following conversation situations: Fun memory talking/listening situation and regrettable memory talking/ listening situation for three minutes each. Lyspect 3.5 was used to collect the data of the finger plethysmogram. Since Lyspect calculates the Lyapunov spectrum, it is possible to obtain the largest Lyapunov exponent (LLE). LLE is an indicator of the fluctuation and shows the degree to which a measure is going away from close proximity to the track in a dynamical system. Before the finger plethysmogram experiment, each participant took the psychological test questionnaire “Anthropophobic Scale.” The scale measures the social phobia trend close to the consciousness of social phobia. It is revealed that there is a remarkable relationship between the fluctuation of the finger plethysmography and anthropophobic tendency scale in talking about a regrettable story in conversation: The participants (N=15) who have a low anthropophobic tendency show significantly more fluctuation of finger pulse waves than the participants (N=17) who have a high anthropophobic tendency (F (1, 31) =5.66, p<0.05). That is, the participants who have a low anthropophobic tendency make conversation flexibly using large fluctuation of biological signal; on the other hand, the participants who have a high anthropophobic tendency constrain a conversation because of small fluctuation. Therefore, fluctuation is not an error but an important drive to make better relationships with others and go towards the development of interaction. In considering mental health, the fluctuation of biological signals would be an important indicator.

Keywords: anthropophobic tendency, finger plethymogram, fluctuation of biological signal, LLE

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Authors: Hassan Youssef Mohamed

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In this paper, we show new wave equations, and by using the equations, we concluded that the strong force and the weak force are not fundamental, but they are quantum effects for electromagnetism. This result is different from the current scientific understanding about strong and weak interactions at all. So, we introduce three evidences for our theory. First, we prove the asymptotic freedom phenomenon in the strong force by using our model. Second, we derive the nuclear shell model as an approximation of our model. Third, we prove that the leptons do not participate in the strong interactions, and we prove the short ranges of weak and strong interactions. So, our model is consistent with the current understanding of physics. Finally, we introduce the electron-positron model as the basic ingredients for protons, neutrons, and all matters, so we can study all particles interactions and nuclear interaction as many-body problems of electrons and positrons. Also, we prove the violation of parity conservation in weak interaction as evidence of our theory in the weak interaction. Also, we calculate the average of the binding energy per nucleon.

Keywords: new wave equations, the strong force, the grand unification theory, hydrogen atom, weak force, the nuclear shell model, the asymptotic freedom, electron-positron model, the violation of parity conservation, the binding energy

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: H. D. Duong, J. I. Rhee

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In this work, gold nanoparticles in star shape (called gold nanostars, GNS) were synthesized and coated by N-(3-aminopropyl) methacrylamide hydrochloride (PA) and mercaptopropionic acid (MPA) for functionalizing their surface by amine and carboxyl groups and then investigated for ROS production. The GNS with big size and multi-tips seem to be superior in singlet oxygen production as compared with that of small GNS and less tips. However, the functioned GNS in small size could also enhance efficiency of singlet oxygen production about double as compared with that of the intact GNS. In combination with methylene blue (MB+), the functioned GNS could enhance the singlet oxygen production of MB+ after 1h of LED750 irradiation and no difference between small size and big size in this reaction was observed. In combination with 5-aminolevulinic acid (ALA), only GNS coated PA could enhance the singlet oxygen production of ALA and the small size of GNS coated PA was a little higher effect than that of the bigger size. However, GNS coated MPA with small size had strong effect on hydroxyl radical production of ALA.

Keywords: 5-aminolevulinic acid, gold nanostars, methylene blue, ROS production

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Authors: Masahiko Suzuki, Takashi Kato , Masahiro Kobayashi

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In our company, the monitoring system for signal equipment has already implemented. So, we can know the state of signal equipment, sitting in the control room or the maintenance center. But this system was installed over 20 years ago, so it cannot stand the needs such as 'more stable operation', 'broadband data transfer', 'easy construction and easy maintenance'. To satisfy these needs, we studied the monitoring system using radio communication as a new method which can realize the operation in the terrible environment along railroads. In these studies, we have developed the terminals and repeaters based on the ZigBee protocol and have implemented the application using two different radio bands simultaneously. At last, we got the good results from the fundamental examinations using the developed equipment.

Keywords: monitoring, radio communication, 2 bands, ZigBee

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Authors: Ching-Yi Yiu, Hui-Chen Hsu

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Objectives: Head and neck cancer (HNC) is a big global health problem in the world. Despite the development of diagnosis and treatment, the overall survival of HNC is still low. The well recognition of the interaction of the host immune system and cancer cells has led to realizing the processes of tumor initiation, progression and metastasis. Many systemic inflammatory responses have been shown to play a crucial role in cancer progression. The pre and post-treatment nutritional and immunological status of HNC patients is a reliable prognostic indicator of tumor outcomes and survivors. Methods: Between July 2020 to June 2022, We have enrolled 60 HNC patients, including 59 males and 1 female, in Chi Mei Medical Center, Liouying, Taiwan. The age distribution was from 37 to 81 years old (y/o), with a mean age of 57.6 y/o. We evaluated the pre-and post-treatment nutritional and immunological status of these HNC patients with body weight, body weight loss, body mass index (BMI), whole blood count including hemoglobin (Hb), lymphocyte, neutrophil and platelet counts, biochemistry including prealbumin, albumin, c-reactive protein (CRP), with the time period of before treatment, post-treatment 3 and 6 months. We calculated the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) to assess how these biomarkers influence the outcomes of HNC patients. Results: We have carcinoma of the hypopharynx in 21 cases with 35％, carcinoma of the larynx in 9 cases, carcinoma of the tonsil and tongue every 6 cases, carcinoma soft palate and tongue base every 5 cases, carcinoma of buccal mucosa, retromolar trigone and mouth floor every 2 cases, carcinoma of the hard palate and low lip each 1 case. There were stage I 15 cases, stage II 13 cases, stage III 6 cases, stage IVA 10 cases, and stage IVB 16 cases. All patients have received surgery, chemoradiation therapy or combined therapy. We have wound infection in 6 cases, 2 cases of pharyngocutaneous fistula, flap necrosis in 2 cases, and mortality in 6 cases. In the wound infection group, the average BMI is 20.4 kg/m2; the average Hb is 12.9 g/dL, the average albumin is 3.5 g/dL, the average NLR is 6.78, and the average PLR is 243.5. In the PC fistula and flap necrosis group, the average BMI is 21.65 kg/m2; the average Hb is 11.7 g/dL, the average albumin is 3.15 g/dL, average NLR is 13.28, average PLR is 418.84. In the mortality group, the average BMI is 22.3 kg/m2; the average Hb is 13.58 g/dL, the average albumin is 3.77 g/dL, the average NLR is 6.06, and the average PLR is 275.5. Conclusion: HNC is a big challenging public health problem worldwide, especially in the high prevalence of betel nut consumption area Taiwan. Besides the definite risk factors of smoking, drinking and betel nut related, the other biomarkers may play significant prognosticators in the HNC outcomes. We concluded that the average BMI is less than 22 kg/m2, the average Hb is low than 12.0 g/dL, the average albumin is low than 3.3 g/dL, the average NLR is low than 3, and the average PLR is more than 170, the surgical complications and mortality will be increased, and the prognosis is poor in HNC patients.

Keywords: nutritional, immunological, neutrophil-to-lymphocyte ratio, paltelet-to-lymphocyte ratio.

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: watershed simulation, WetSpa, stream flow, flood prediction

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Authors: Makram Ben Jeddou

Abstract:

The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

Procedia PDF Downloads 486

Authors: Noha El-Gohary, Thanaa El-Shater, A. A. Mahfouz, M. M. Sakr

Abstract:

Searching for high power conversion efficiency and long lifetime are important goals when designing a power supply subsystem for satellite applications. To fulfill these goals, this paper presents a power supply subsystem for small satellites in which flywheel energy storage system is used as a secondary power source instead of chemical battery. In this paper, the model of flywheel energy storage system is introduced; a DC bus regulation control algorithm for charging and discharging of flywheel based on space vector pulse width modulation technique and motor current control is also introduced. Simulation results showed the operation of the flywheel for charging and discharging mode during illumination and shadowed period. The advantages of the proposed system are confirmed by the simulation results of the power supply system.

Keywords: small-satellites, flywheel energy storage system, space vector pulse width modulation, power conversion

Procedia PDF Downloads 384

Authors: Otman Jai, Otman Elhajjaji, Jaouad Tajmouati

Abstract:

Several neutronic calculation codes must be used to solve the equation for different levels of discretization which all necessitate a specific modelisation. This chain of such models, known as a calculation scheme, leads to the knowledge of the neutron flux in a reactor from its own geometry, its isotopic compositions and a cross-section library. Being small in size, the 'Slowpoke-2' reactor is difficult to model due to the importance of the leaking neutrons. In the paper, the simulation model is presented (geometry, cross section library, assumption, etc.), and the results obtained by DRAGON4/DONJON4 codes were compared to the calculations performed with Monte Carlo code MCNP using detailed geometrical model of the reactor and the experimental data. Criticality calculations have been performed to verify and validate the model. Since created model properly describes the reactor core, it can be used for calculations of reactor core parameters and for optimization of research reactor application.

Keywords: transport equation, Dragon4, Donjon4, neutron flux, effective multiplication factor

Procedia PDF Downloads 450

Authors: Salma Aboussalam, Karima Khalil, Khalid Elkalay

Abstract:

In order to understand the structure, functioning, and current state of the Moroccan Mediterranean Sea ecosystem, an Ecopath mass balance model was applied. The model was based on 31 functional groups, which included 21 fish species, 7 invertebrates, 2 primary producers, and one detritus group. The trophic interactions between these groups were analyzed, and the system's average trophic transfer efficiency was found to be 23%. The total primary production and total respiration were calculated to be greater than 1, indicating that the system produces more energy than it respires. The ecosystem was found to have a high level of respiration and consumption flows, and indicators of stability and development showed low values for the Finn cycle index (13.97), system omnivory index (0.18), and average Finn path length (3.09), indicating that the ecosystem is disturbed and has a linear rather than web-like trophic structure. Keystone species were identified using the keystone index and mixed trophic impact analysis, with other demersal invertebrates, zooplankton, and cephalopods found to have a significant impact on other groups.

Keywords: ecopath, food web, trophic flux, moroccan mediterranean sea

Procedia PDF Downloads 56

Authors: Mudavath Raju, Bhaskar Gugulothu, B. Rajendra Naik

Abstract:

The rapid advances in Very Large Scale Integration (VLSI) technology has resulted in the reduction of minimum feature size to sub-quarter microns and switching time in tens of picoseconds or even less. As a result, the degradation of high-speed digital circuits due to signal integrity issues such as coupling effects, clock feedthrough, crosstalk noise and delay uncertainty noise. Crosstalk noise in VLSI interconnects is a major concern and reduction in VLSI interconnect has become more important for high-speed digital circuits. It is the most effectively considered in Deep Sub Micron (DSM) and Ultra Deep Sub Micron (UDSM) technology. Increasing spacing in-between aggressor and victim line is one of the technique to reduce the crosstalk. Guard trace or shield insertion in-between aggressor and victim is also one of the prominent options for the minimization of crosstalk. In this paper, far end crosstalk noise is estimated with mutual inductance and capacitance RLC interconnect model. Also investigated the extent of crosstalk in capacitive and inductively coupled interconnects to minimizes the same through shield insertion technique.

Keywords: VLSI, interconnects, signal integrity, crosstalk, shield insertion, guard trace, deep sub micron

Procedia PDF Downloads 170

Authors: Mananya Meenakorn

Abstract:

The purpose of this research is to study the relationship customer perception and brand value of cosmetics in the view of customers in Thailand. The research is quantitative research using the survey method by questionnaire. Data were collected from female cosmetics consumer that residents in Bangkok, aged between 25-55 years. Researchers have determined the size of the sample by using Taro Yamane technic a total of 400 people. The study found the Shiseido cosmetics brand image always come with the new products innovation is in the height level. The average was 3.812, second is Shiseido brand has used innovation to produce the product for 3.792. And brand Shiseido looks luxury with an average of 3.707 respectively. In additional in terms of Lancôme cosmetic brand found the brand image is luxury at the height levels for 4.170 average. The seductive glamor is considered in the moderate with an average of 3.822 respectively.

Keywords: brand image, international fashion dress, values, working women

Procedia PDF Downloads 203

Authors: Pranav Gulati, Isha Sharma

Abstract:

Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

Procedia PDF Downloads 253