Search results for: short course

Authors: Nur H. Ahmad, Silvia S. Inge, Vanessa A. Julliete, A. Veraditias, Laila F. Febinda

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Abdominal obesity is a risk factor for metabolic syndrome and mostly found in adolescents. Waist circumference is related to abdominal obesity which has a significant effect on the increase of blood pressure. Inulin is one of prebiotic, that has health benefits by offering the potential for lipid management, that can be useful to decrease the risk factor of metabolic syndrome. The aim of the research is to evaluate the effect of 10 gram inulin-substituted ice cream in waist circumference and blood pressure of abdominal obesity adolescents. Inulin had the ability to produce Short Chain Fatty Acid which can improve blood pressure and waist circumference. Systolic blood pressure was significantly decreased in the treatment group (p=0.028) with the mean of reduction 7.35 ± 11.59 mmHg. However, diastolic blood pressure and waist circumference showed no significant effect. Waist circumference, systolic blood pressure and diastolic blood pressure was decreased in control group. These results suggest that inulin-substituted ice cream used as therapeutics and prevention for the early onset of metabolic syndrome.

Keywords: blood pressure, inulin, metabolic syndrome, waist circumference

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Authors: Marjan Ghazisaeedi, Azadeh Bashiri

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Background: Attention-Deficit/Hyperactivity Disorder(ADHD), is one of the most common psychiatric disorders in early childhood that in addition to its main symptoms provide significant deficits in the areas of educational, social and individual relationship. Considering the importance of rehabilitation in ADHD patients to control these problems, this study investigated the advantages of computer-based cognitive training in these patients. Methods: This review article has been conducted by searching articles since 2005 in scientific databases and e-Journals and by using keywords including computerized cognitive rehabilitation, computer-based training and ADHD. Results: Since drugs have short term effects and also they have many side effects in the rehabilitation of ADHD patients, using supplementary methods such as computer-based cognitive training is one of the best solutions. This approach has quick feedback and also has no side effects. So, it provides promising results in cognitive rehabilitation of ADHD especially on the working memory and attention. Conclusion: Considering different cognitive dysfunctions in ADHD patients, application of the computerized cognitive training has the potential to improve cognitive functions and consequently social, academic and behavioral performances in patients with this disorder.

Keywords: ADHD, computer-based cognitive training, cognitive functions, rehabilitation

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Authors: Derick Shi-Chen Ou, Liang-Yu Chen

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Background: Acupuncture, a potential alternative, and complementary therapy revealed insufficient evidence in depression treatment. The efficacy of acupuncture treatment was still uncertainty. To evaluate the effect of acupuncture in treating depression, the randomized controlled trials (RCTs) were examined. Methods: RCTs of the acupuncture therapy in treating major depression were searched from MEDLINE from 2007 to 2017. Keywords used for searching strategy included acupuncture, acupoint, and major depressive disorder. Results: Among the nine RCTs, four studies demonstrated great improvement in acupuncture treatment and five studies revealed the effectiveness of acupuncture intervention in medication. General trends suggest that acupuncture treatment is as effective as antidepressants with minimal side effects. Conclusion: Despite the promising results from the RCTs, there are still a variety of limitations, including small sample size, imprecise enrollment criteria, difficulties with blinding, randomization, short duration of study and lack of longitudinal follow-up. Therefore, the evidence that acupuncture as an alternative therapy for depression is inconclusive. More rigorously designed RCTs should be conducted in the future.

Keywords: acupuncture, major depressive disorders, randomized clinical trials, antidepressants

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Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Zarrin Nasri

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Microwave irradiation is an innovative technology in the petroleum industry. This kind of energy has been considered to convert vacuum residue of oil refineries into useful products. The advantages of microwaves energy are short time, fast heating, high energy efficiency, and precise process control. In this paper, the effects of catalyst type and amount have been investigated on upgrading of vacuum residue using microwave irradiation. The vacuum residue used in this research is from Tehran oil refinery, Iran. Additives include different catalysts, active carbon as sensitizer, and sodium borohydride as a solid hydrogen donor. Various catalysts contain iron, nickel, molybdenum disulfide, iron oxide and copper. The amount of catalysts in two cases of presence and absence of sodium borohydride have been evaluated. The objective parameters include temperature, asphaltene, viscosity, and API. The specifications of vacuum residue are API, 8.79, viscosity, 16391 cSt (60°C), asphaltene, 13.3 wt %. The results show that there is a significant difference between the effects of catalysts. Among the used catalysts, Fe powder is the best catalyst for upgrading vacuum residue using microwave irradiation and resulted in asphaltene reduction, 31.3 %; viscosity reduction, 76.43 %; and 23.43 % in API increase.

Keywords: asphaltene, microwave, upgrading, vacuum residue, viscosity

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Ramzi Rihane, Yassine Benayed

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Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee, Yu-Cheng Kuo

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In order to understand whether there is a better than the learning function of learning methods and improve the CAD Courses for enterprise’s design human resource development, this research is applied in learning practical learning computer graphics software. In this study, Revit building information model for learning content, design of two different modes of learning curriculum to learning, learning functions, respectively, and project learning. Via a post-test, questionnaires and student interviews, etc., to study the effectiveness of a comparative analysis of two different modes of learning. Students participate in a period of three weeks after a total of nine-hour course, and finally written and hands-on test. In addition, fill in the questionnaire response by the student learning, a total of fifteen questionnaire title, problem type into the base operating software, application software and software-based concept features three directions. In addition to the questionnaire, and participants were invited to two different learning methods to conduct interviews to learn more about learning students the idea of two different modes. The study found that the ad hoc short-term courses in learning, better learning outcomes. On the other hand, functional style for the whole course students are more satisfied, and the ad hoc style student is difficult to accept the ad hoc style of learning.

Keywords: development, education, human resource, learning

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Zhe Li, Aihua Cai

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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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Authors: Heidi Ahonen

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Since antiquity, many cultures have seemingly known the power of low frequencies, incorporating them in healing practices through drumming, singing, humming, etc. Many music therapists recognize there is something in music that is transformative enough to make a difference in people’s lives. This paper summarizes the key findings of several low-frequency research with various client populations conducted by the author. Utilizing low-frequency sound (30 or 40 Hz) may have diverse therapeutic impacts: (1) Calming effect – decreased agitation (autism, brain injury, AD, dementia) (2) Muscle relaxation (CP & spasticity & pain/after surgery patients, MS, fibromyalgia) (3) Relaxation/stress release (anxiety, stress, PTSD, trauma, insomnia) (4) Muscular/motor functioning/ decrease of tremor (CP, MS, Parkinson) (5) Increase in alertness, cognitive awareness & short-term memory function (brain injury, severe global developmental delay, AD) (6) Increased focus (AD, PTSD, trauma). The paper will conclude by presenting ideas informing the clinical practice. Future studies need to investigate what frequencies are effective for particular client populations and why, what theories can explain the effect, and finally, something that has been long debated - is it auditive or kinaesthetic stimulation or the combination of both that is effective?

Keywords: low frequency, 40 Hz, sound, neuro disability

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Authors: Mehdi Ganjkhani, Sobhan Badakhshan, Seyedvahid Hosseini

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Power plants exploit striking proportion of underground water consumption. Correspondingly, natural gas-fired power plants need less water than the other conventional power plants. Therefore, shifting unit commitment planning toward these power plants would help to save water consumption. This paper discusses the impacts of water consumption limitation on natural gas consumption and vice versa as a short-term water consumption management solution. To do so, conventional unit commitment problem is extended by adding water consumption and natural gas constraints to the previous constrains. The paper presents the impact of water saving on natural gas demands as well as natural gas shortage on water demand. Correspondingly, the additional cost of electricity production according to the aforementioned constraints is evaluated. Finally, a test system is applied to investigate potentials and impacts of water saving and natural gas shortage. Different scenarios are conducted and the results are presented. The results of the study illustrate that in order to use less water for power production it needs to use more natural gas. Meanwhile, natural gas shortage causes to utilize more amount of water in aggregate.

Keywords: electric energy generation system, underground water sources, unit commitment, water consumption saving, natural gas

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Authors: Zhepeng Rui, Zhenyu Gu, Caitilin de Bérigny

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In the current study, we designed an interactive meditation and brain painting application to cultivate users’ creativity, promote meditation, reduce stress, and improve cognition while attempting to learn a foreign language. User tests and data analyses were conducted on 42 male and 42 female participants to better understand sex-associated psychological and aesthetic differences. Our method utilized brain-computer interfaces to import meditation and attention data to create artwork in meditation-based applications. Female participants showed statistically significantly different language learning outcomes following three meditation paradigms. The art style of brain painting helped females with language memory. Our results suggest that the most ideal methods for promoting memory attention were meditation methods and brain painting exercises contributing to language learning, memory concentration promotion, and foreign word memorization. We conclude that a short period of meditation practice can help in learning a foreign language. These findings provide new insights into meditation, creative language education, brain-computer interface, and human-computer interactions.

Keywords: brain-computer interface, creative thinking, meditation, mental health

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Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: R. M. Chandler, A. J. Stringer

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In adults, short bursts of high-intensity exercise (intensities between 80-95% of maximum heart rates) increase cardiovascular and metabolic function without the time investment of traditional aerobic training. Similar improvements in various health indices are also becoming increasingly evident in children in countries other than the United States. In the United States, physical education programs have become shorter in length and fewer in frequency. With this in the background, it is imperative that health and physical educators delivered well-organized and focused fitness programs that can be tolerated across many different somatotypes. Perhaps the least effective lag-time in a US physical education (PE) class is the first 10 minutes, a time during which children warm up. Replacing a traditional PE warmup with a 10 min high-intensity excise protocol is a time-efficient method to impact health, leaving as much time for other PE material such as skill development, motor behavior development as possible. This supplemented 10 min high-intensity exercise increases cardiovascular function as well as induces favorable body composition changes in as little as six weeks with further enhancement throughout a semester of activity. The supplemental high-intensity exercise did not detract from the PE lesson outcomes.

Keywords: cardiovascular fitness, high intensity interval training, high intensity exercise, pediatric

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Authors: Raghad Dwaik

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It is well known in language acquisition literature that a mere understanding of a reading text is not enough to help students build proficiency in comprehension. Students should rather follow understanding by attempting to express what has been understood by pushing their competence to the limit. Learners' attempt to push their competence was given the term "comprehensible output" by Swain (1985). Teachers in large classes, however, find it sometimes difficult to give all students a chance to communicate their views or to share their ideas during the short class time. In most cases, students who are outgoing dominate class discussion and get more opportunities for practice which leads to ignoring the shy students totally while helping the good ones become better. This paper presents the idea of using Google Classroom features of posting and commenting to allow students who hesitate to participate in class discussions about a reading text to write their views on the wall of a Google Classroom and share them later after they have received feedback and comments from classmates. Such attempts lead to developing their proficiency through additional practice in comprehensible output and to enhancing their confidence in themselves and their views. It was found that virtual classroom interaction would help students maintain vocabulary, use more complex structures and focus on meaning besides form.

Keywords: learning groups, reading TESOL, Google Classroom, comprehensible output

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Authors: Stephan Koehler, Thomas Friedli

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Performance measurement has evolved over time from a unidimensional short-term efficiency focused approach into a balanced multidimensional approach. Today, integrated performance measurement frameworks are often used to avoid local optimization and to encourage continuous improvement of an organization. In literature, the multidimensional characteristic of performance measurement is often described by competitive priorities. At the same time, on the highest abstraction level an effectiveness and efficiency dimension of performance measurement can be distinguished. This paper aims at a better understanding of the composition of effectiveness and efficiency and their relation in pharmaceutical quality control labs. The research comprises a lab-specific operationalization of effectiveness and efficiency and examines how the two dimensions are interlinked. The basis for the analysis represents a database of the University of St. Gallen including a divers set of 40 different pharmaceutical quality control labs. The research provides empirical evidence that labs with a high effectiveness also accompany a high efficiency. Lab effectiveness explains 29.5 % of the variance in lab efficiency. In addition, labs with an above median operational excellence performance have a statistically significantly higher lab effectiveness and lab efficiency compared to the below median performing labs.

Keywords: empirical study, operational excellence, performance measurement, pharmaceutical quality control lab

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Authors: Spyridon Plakoudas

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After the capture of Al-Raqqah and the defeat of the short-lived Islamic Caliphate in 2017, everyone predicted the end of ISIS. However, ISIS proved far more resilient than initially thought. The militant group quickly regrouped from its defeat and started a low-intensity guerrilla campaign in central Iraq (near Kirkuk and Mosul) and north-eastern Syria (near Deir ez-Zorr). At the same time, ISIS doubled down on its cyber-campaign; actually, ISIS is as active on the cyber-domain as during the peak of its power in 2015. This paper, a spin-off paper from a co-authored book on the Syrian Civil War (due to be published by Rowman and Littlefield), intends to examine how ISIS operates in the cyber-domain and how this "Cyber-Caliphate" under re-construction is associated with its post-2017 strategy. This paper will draw on the discipline of War Studies (with an emphasis on Cyber-Security and Insurgency / Counter-Insurgency) and will benefit from the insights of interviewed experts on the field (e.g., Hassan Hasssan). This paper will explain how the successful operation of ISIS in the cyber-space preserves the myth of the “caliphate” amongst its worldwide followers (against the odds) and sustains the group’s ongoing insurgency in Syria and Iraq; in addition, this paper will suggest how this cyber-threat can be countered best.

Keywords: ISIS, cyber-jihad, Syrian Civil War, cyber-terrorism, insurgency and counter-insurgency

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Authors: Sufia Maroof

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This empirical study investigated the web-translations of five Pakistani public offices (FPSC, FIA, HEC, USB, and Ministry of Finance) offering Urdu tab as an option to access information on their official websites. Triangulation of quantitative and qualitative research design informed the researcher of the semantic, lexical and syntactic caveats in these translations. The study hypothesized that majority of the Pakistani population is oblivious of the Supreme Court’s amendments in language policy concerning national and official language; hence, Urdu web-translations of the public departments have not been accessed effectively. Firstly, the researcher conducted an online survey, comprising of two sections, close ended and short answer based questions. Secondly, the researcher compiled corpus of the five selected websites in a tabular form to compare the data. Thirdly, the administrators of the departments had been contacted regarding the methods of translation and the expertise of the personnel involved. The corpus was assessed for TQA after examining the lexical, semantic, syntactical and technical alignment inaccuracies and imperfections. The study suggests the public offices to invest in their Urdu webs by either hiring expert translators or engaging expertise of a translation agency for this project to offer quality translation to public.

Keywords: machine translations, public offices, Urdu translations, websites

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Authors: Abdulfetah Shobole, Arif Karakas, Ugur Savas Selamogullari, Mustafa Baysal

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The concern of reducing emissions of Co2 from the fossil fuel generating units and using renewable energy sources increased in our world. Due this fact the integration ratio of wind farms to grid reached 20-30% in some part of our world. With increased integration of large MW scaled wind farms to the electric grid, the stability of the electrical system is a great concern. Thus, operators of power systems usually deman the wind turbine generators to obey the same rules as other traditional kinds of generation, such as thermal and hydro, i.e. not affect the grid stability. FACTS devices such as SVC or STATCOM are mostly installed close to the connection point of the wind farm to the grid in order to increase the stability especially during faulty conditions. In this paper wind farm with DFIG turbine type and STATCOM are dynamically modeled and simulated under three phase short circuit fault condition. The dynamic modeling is done by DigSILENT PowerFactory for the wind farm, STATCOM and the network. The simulation results show improvement of system stability near to the connection point of the STATCOM.

Keywords: DFIG wind turbine, statcom, dynamic modeling, digsilent

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Authors: Said Yousif Khairi

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Being a developing economy, imports of capital, raw materials and manufactories goods are vital for sustainable economic growth. In 2006, Libya imported LD 8 billion (US$ 6.25 billion) which composed of mainly machinery and transport equipment (49.3%), raw material (18%), and food products and live animals (13%). This represented about 10% of GDP. Thus, it is pertinent to investigate factors affecting the amount of Libyan imports. An econometric model representing the aggregate import demand for Libya was developed and estimated using the bounds test procedure, which based on an unrestricted error correction model (UECM). The data employed for the estimation was from 1970–2010. The results of the bounds test revealed that the volume of imports and its determinants namely real income, consumer price index and exchange rate are co-integrated. The findings indicate that the demand for imports is inelastic with respect to income, index price level and The exchange rate variable in the short run is statistically significant. In the long run, the income elasticity is elastic while the price elasticity and the exchange rate remains inelastic. This indicates that imports are important elements for Libyan economic growth in the long run.

Keywords: import demand, UECM, bounds test, Libya

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Authors: Harald Haas, Andrea Plaschke

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Many of the contemporary major conflicts on this earth could not be solved so far, they either are perpetuated, or they are reflated again and again. Efforts of purely political conflict management or -resolution aim merely at the symptoms of conflict, not its roots. These roots are, in almost every case, also psychological ones. Thus, this contribution aims to shed light on the roots of one of the best known and longest-lasting conflicts: the Palestinian-Israeli one. Methodologies used were the compilation of existing scientific resources, field research in Palestine and Israel, as well as tests conducted with the Adult Attachment Projective in Palestine and Israel. Findings show that the majority of Palestinian, as well as Israeli test participants, show a disorganised attachment pattern which, in connection with the assumption of collective traumatization, seem to be a major obstacle to a lasting and peaceful conflict-resolution between these two peoples. There appears to be no short-term solution for this conflict, especially not within the range of usual Western legislative periods. Both sides ought to be provided with a kind of 'safe haven' over a long period of time, accompanied by a framework of various arrangements of coping with trauma, building lasting and secure relationships, as well as raising and educating present and future generations of Palestinians and Israelis for peace and co-operation with each other.

Keywords: conflict-management, trauma, political psychology, attachment theory

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Authors: Zubier Arfan, Paul Johnson

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The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model.

Keywords: market-making, market-microsctrucure, stochastic volatility, quantitative trading

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Authors: Nur Allisha Othman, Rosnah Shamsudin, Zaulia Othman, Siti Hajar Othman

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Mitigating short storage life of fruit like banana uses minimally process or known as fresh cut can contribute to the growing demand especially in South East Asian countries. The effect of different types of packaging material on fresh-cut Nipah (Musa acuminata balbisiana) were studied. Fresh cut banana cultivar (cv) Nipah are packed in polypropylene plastic (PP), low density polypropylene plastic (LDPE), polymer plastic film (shrink wrap) and polypropylene container as control for 12 days at low temperature (4ᵒC). Quality of physical and chemical evaluation such as colour, texture, pH, TA, TSS, and vitamin C were examined every 2 days interval for 12 days at 4ᵒC. Result shows that the PP is the most suitable packaging for banana cv Nipah because it can reduce respiration and physicochemical quality changes of banana cv Nipah. Different types of packaging significantly affected quality of fresh-cut banana cv Nipah. PP bag was the most suitable packaging to maintain quality and prolong storage life of fresh-cut banana cv Nipah for 12 days at 4ᵒC.

Keywords: physicochemical, PP, LDPE, shrink wrap, browning, respiration

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Authors: Fayssal Amrane, Azeddine Chaiba, Bruno Francois

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In this paper, design and experimental study based on Direct Power Control (DPC) of DFIG is proposed for Stand-alone mode in Variable Speed Wind Energy Conversion System (VS-WECS). The proposed IDPC method based on robust IP (Integral-Proportional) controllers in order to control the Rotor Side Converter (RSC) by the means of the rotor current d-q axes components (Ird* and Irq*) of Doubly Fed Induction Generator (DFIG) through AC-DC-AC converter. The implementation is realized using dSPACE dS1103 card under Sub and Super-synchronous operations (means < and > of the synchronous speed “1500 rpm”). Finally, experimental results demonstrate that the proposed control using IP provides improved dynamic responses, and decoupled control of the wind turbine has driven DFIG with high performances (good reference tracking, short response time and low power error) despite for sudden variation of wind speed and rotor references currents.

Keywords: Direct Power Control (DPC), Doubly fed induction generator (DFIG), Wind Energy Conversion System (WECS), Experimental study.

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Authors: Duy M. P. Vo, Cornelia Sennewald, Gerald Hoffmann, Chokri Cherif

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The development of solutions to improve the resistance of buildings to short-term dynamic loads, particularly impact load, is driven by the urgent demand worldwide on securing human life and critical infrastructures. The research training group GRK 2250/1 aims to develop mineral-bonded composites that allow the fabrication of thin-layered strengthening layers providing available concrete members with enhanced impact resistance. This paper presents the development of 3D woven wire cellular structures that can be used as innovative reinforcement for targeted composites. 3D woven wire cellular structures are truss-like architectures that can be fabricated in an automatized process with a great customization possibility. The specific architecture allows this kind of structures to have good load bearing capability and forming behavior, which is of great potential to give strength against impact loading. An appropriate combination of topology and material enables an optimal use of thin-layered reinforcement in concrete constructions.

Keywords: 3D woven cellular structures, ductile behavior, energy absorption, fiber-based reinforced concrete, impact resistant

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Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

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The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

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Authors: Ryan M. Monti, Bijal Mehta

Abstract:

In cases of massive pulmonary embolism, defined as acute pulmonary embolism presenting with systemic hypotension or right ventricular dysfunction and impending failure, there is indication that unconventional therapies, such as phosphodiesterase inhibitors, endothelin receptor antagonists, and/or prostacyclin analogs may decrease the morbidity and mortality. Based on the premise that dilating the pulmonary artery will decrease the pulmonary vascular pressure, while simultaneously decreasing the aggregation of platelets, it can be hypothesized that increased blood flow through the pulmonary artery will decrease right heart strain and subsequent morbidity and mortality. While this theory has yet to be formally studied, the recommendations for treating massive pulmonary embolism with phosphodiesterase inhibitors, endothelin receptor antagonists, and/or prostacyclin analogs in conjunction with the current standards of care in massive pulmonary embolism should be formally studied. In particular, patients with massive PE who are unable to undergo thrombolysis/surgical intervention may be the ideal population to study the use of these treatments to determine any decrease in mortality and morbidity (short term and long term).

Keywords: acute pulmonary thromboembolism, treatment of pulmonary embolism, use of phosphodiesterase inhibitors, endothelin receptor antagonists, prostacyclin analogs in PE

Procedia PDF Downloads 225

Authors: Sheraz Ahmad Choudhary

Abstract:

Health plays a vital role in the growth. The study examined the effect of health indicator on the growth of Pakistan. ARDL model is used to check the growth rate which is affected by the health by using the time series date of Pakistan from 1990 to 2017. Health indicator, fertility rate, life expectancy, foreign direct investment, and infant mortality rate are variables Where the unit root is applied to check the stationarity of the model. consequences find a significant relationship between GDP, foreign direct investment, fertility rate, and life expectancy in the short run, whereas mortality rate effected negatively to economic growth but have significant values. In the long run, foreign direct investment (FDI) and fertility rate(FR) have significantly influenced the GDP. The results show thateconomic growth is positively stimulated by most of the health indicators. The study accomplishes that nations can achieve a high level of economic growth by increasing wellbeing human capital.

Keywords: economic growth, health expenditures, fertility rate, human capital, life expectancy, foreign direct investment, and infant mortality rate

Procedia PDF Downloads 129