Search results for: deep and shallow strategies

Authors: Ng Mei Han, Nu'man Abdul Hadi

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Extraction of ferulic acid from palm pressed fiber using deep eutectic solvent (DES) of choline chloride-acetic acid (ChCl-AA) and choline chloride-citric acid (ChCl-CA) are reported. Influence of water content in DES on the extraction efficiency was investigated. ChCl-AA and ChCl-CA experienced a drop in viscosity from 9.678 to 1.429 and 22.658 ± 1.655 mm2/s, respectively as the water content in the DES increased from 0 to 50 wt% which contributed to higher extraction efficiency for the ferulic acid. Between 41,155 ± 940 mg/kg ferulic acid was obtained after 6 h reflux when ChCl-AA with 30 wt% water was used for the extraction compared to 30,940 ± 621 mg/kg when neat ChCl-AA was used. Although viscosity of the DES could be improved with the addition of water, there is a threshold where the DES could tolerate the presence of water without changing its solvent behavior. The optimum condition for extraction of ferulic acid from palm pressed fiber was heating for 6 h with DES containing 30 wt% water.

Keywords: deep eutectic solvent, extraction, ferulic acid, palm fibre

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Authors: Theodorou Kyriaki, Ypsilantis George

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Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

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Authors: Chiau Yuan Lim, Hayyiratul Fatimah Mohd Zaid, Fai Kait Chong

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Deep Eutectic Solvent (DES) is used in various applications due to its simplicity in synthesis procedure, biodegradable, inexpensive and easily available chemical ingredients. Graphene Oxide is a popular catalyst that being used in various processes due to its stacking carbon sheets in layer which theoretically rapid up the catalytic processes. In this study, choline chloride based DESs were synthesized and ChCl-PEG(1:4) was found to be the most effective DES in performing desulfurization, which it is able to remove up to 47.4% of the sulfur content in the model oil in just 10 minutes, and up to 95% of sulfur content after repeat the process for six times. ChCl-PEG(1:4) able to perform up to 32.7% desulfurization on real diesel after 6 multiple stages. Thus, future research works should focus on removing the impurities on real diesel before utilising DESs in petroleum field.

Keywords: choline chloride, deep eutectic solvent, fuel desulfurization, graphene oxide

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Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

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Based on the geodynamic environment, basic geological characteristics of minerals and so on, gold deposits in China are divided into 11 categories, of which tectonic fracture altered rock, mid-intrudes and contact zone, micro-fine disseminated and continental volcanic types are the main prospecting kinds. The metallogenic age of gold deposits in China is dominated by the Mesozoic and Cenozoic. According to the geotectonic units, geological evolution, geological conditions, spatial distribution, gold deposits types, metallogenic factors etc., 42 gold concentration areas are initially determined and have a concentrated distribution feature. On the basis of the gold exploration density, gold concentration areas are divided into high, medium and low level areas. High ones are mainly distributed in the central and eastern regions. 93.04% of the gold exploration drillings are within 500 meters, but there are some problems, such as less and shallower of drilling verification etc.. The paper discusses the resource potentials of gold deposits and proposes the future prospecting directions and suggestions. The deep and periphery of old mines in the central and eastern regions and western area, especially in Xinjiang and Qinghai, will be the future key prospecting one and have huge potential gold reserves. If the exploration depth is extended to 2,000 meters shallow, the gold resources will double.

Keywords: gold deposits, gold deposits types, gold concentration areas, prospecting, resource potentiality

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Authors: Yukiko Sasaki Alam, Shahid Alam

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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: syntactic parsing, error analysis, machine translation, deep parsing

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Authors: Regina Streltsov

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The Archipelago of the Azores in the NE Atlantic is a hot spot of marine biodiversity, both pelagic and demersal. Epinephelus marginatus is a solitary species commonly observed in these waters, with distinct territorial/residential behaviors from their post- larva and juvenile stages to the adult phase. Being commercially high valued species, about 13% of all groupers (Family Epinephelidae) face an increasing pressure that has produced known impacts in both the abundance and distribution of this group of fishes. Epinephelus marginatus is currently assessed by the IUCN as a vulnerable species. Dusky gropers inhabit rocky bottoms from shallow waters down to 200 m. Juveniles are usually found in shallow shoreline waters. Population dynamics of juveniles can lead to a better understanding of the competition for resources and predation and further conservation measures that must be taken upon dusky groupers. This study is carried out in rocky reefs from two sheltered bays on the south and north coast of the island in two different spots with four sampling sites in total. Using Transects individuals are counted at the peak of high tide and all abiotic factors are recorded. Our goal is to complete a statistically significant number of observations in order to detail these populations and to better understand their dynamics and dimension.

Keywords: Azores, dusky groupers, Epinephelus marginatus, population dynamics

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Authors: Antonio Oliveira, Rute F. Meneses, Nuno Trigueiros-Cunha

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Tinnitus is commonly defined as an aberrant perception of sound without external stimulus. It is a chronic condition, with consequences on the QOL. The coping strategies used were not always effective and coping was identified as a predictor of QOL in individuals with tinnitus, which reinforces the idea that in health the use of effective coping styles should be promoted. This work intend to verify relations between coping strategies assessed by BriefCope in subjects with tinnitus and variables such as gender, age and severity of tinnitus measured by THI and the Visual Analogue Scale and also hearing and hyperacusis. The results indicate that there are any statistically significant relationships between the variables assessed in relation to the results of BriefCope except in the Visual Analogue Scale. These results, indicating no relationship between almost all variables, reinforce the need for further study of coping strategies use by these patients.

Keywords: Brief Cope, coping strategies, quality of live, THI, Tinnitus

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Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

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A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Halima Musa Kamilu

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This paper discusses the effective strategies for teaching English language to learners in primary schools in Nigeria. English language development is the systematic use of instructional strategies designed to promote the acquisition of English by pupils in primary schools whose primary language is not English. Learning a second language is through total immersion. These strategies support this learning method, allowing pupils to have the knowledge of English language in a pattern similar to the way they learned their native language through regular interaction with others who already know the language. The focus is on fluency and learning to speak English in a social context with native speakers. The strategies allow for effective acquisition. The paper also looked into the following areas: visuals that reinforce spoken or written words, employ gestures for added emphasis, adjusting of speech, stressing of high-frequency vocabulary words, use of fewer idioms and clarifying the meaning of words or phrases in context, stressing of participatory learning and maintaining a low anxiety level and boosting of enthusiasm. It recommended that the teacher include vocabulary words that will make the content more comprehensible to the learner.

Keywords: effective, strategies, teaching, beginners and primary schools

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Authors: Ayshan Gurbanova

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Despite based on the fact that drill bit which is the smallest part of bottom hole assembly costs only in between 10% and 15% of the total expenses made, they are the first equipment that is in contact with the formation itself. Hence, it is consequential to choose the appropriate type and dimension of drilling bit, which will prevent majority of problems by not demanding many tripping procedure. However, within the advance in technology, it is now seamless to be beneficial in the terms of many concepts such as subsequent time of operation, energy, expenditure, power and so forth. With the intention of applying the method to Azerbaijan, the field of Shallow Water Absheron Peninsula has been suggested, where the mainland has been located 15 km away from the wildcat wells, named as “NKX01”. It has the water depth of 22 m as indicated. In 2015 and 2016, the seismic survey analysis of 2D and 3D have been conducted in contract area as well as onshore shallow water depth locations. With the aim of indicating clear elucidation, soil stability, possible submersible dangerous scenarios, geohazards and bathymetry surveys have been carried out as well. Within the seismic analysis results, the exact location of exploration wells have been determined and along with this, the correct measurement decisions have been made to divide the land into three productive zones. In the term of the method, Electric Impulse Technology (EIT) is based on discharge energies of electricity within the corrosivity in rock. Take it simply, the highest value of voltages could be created in the less range of nano time, where it is sent to the rock through electrodes’ baring as demonstrated below. These electrodes- higher voltage powered and grounded are placed on the formation which could be obscured in liquid. With the design, it is more seamless to drill horizontal well based on the advantage of loose contact of formation. There is also no chance of worn ability as there are no combustion, mechanical power exist. In the case of energy, the usage of conventional drilling accounts for 1000 𝐽/𝑐𝑚3 , where this value accounts for between 100 and 200 𝐽/𝑐𝑚3 in EIT. Last but not the least, from the test analysis, it has been yielded that it achieves the value of ROP more than 2 𝑚/ℎ𝑟 throughout 15 days. Taking everything into consideration, it is such a fact that with the comparison of data analysis, this method is highly applicable to the fields of Azerbaijan.

Keywords: drilling, drill bit cost, efficiency, cost

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Authors: Hsin-Yi Lien

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The study explored the role of metacognition in foreign language anxiety on a sample of 411 Taiwanese students of English as a Foreign Language. The reading strategy inventory was employed to evaluate the tertiary learners’ level of metacognitive awareness and a semi-structured background questionnaire was also used to examine the learners’ perceptions of their English proficiency and satisfaction of their current English learning. In addition, gender and academic level differences in employment of reading strategies were investigated. The results showed the frequency of reading strategy use increase slightly along with academic years and males and females actually employ different reading strategies. The EFL tertiary learners in the present study utilized cognitive strategies more frequently than metacognitive strategies or support strategies. Male students use metacognitive strategy more often while female students use cognitive and support strategy more frequently.

Keywords: cognitive strategy, gender differences, metacognitive strategy, support strategy

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Authors: Lama Ajinah

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Luxury brands witnessed continuous growth which followed women’s desire towards individual distinctiveness and social glare. Bags are a woman’s best friend either for aesthetic or functional purposes when she leaves her home for leisure or work. One way of women constant aspiration for being distinguished while reflecting their wealth is through handbags. Subsequently, the demand and attraction by consumers towards the dazzle of luxurious brands for personal pleasure and social status have flourished. According to the literature review, a visual analysis on luxury brands has been explored yet a focus on bags was not discussed in details. Hence, a deep analysis will be dedicated on the two segments by showcasing examples of high-end bag advertising. The research is conducted to understand advertising strategies used in promoting for luxurious products. Furthermore, the paper explores the definition of the term luxury, the condition in which it is used in, and the visual language used along with the term. As luxury is an indicator of superior satisfaction, it is obtained on two levels: a personal and a social level. The examples of luxury brand ads are selected from the last five years to uncover the latest, most common strategies used to promote for luxurious brands. The methods employed in this paper consist of literature review, semiotic analysis, and content analysis. The researcher concludes with revealing the methods used in advertising while categorizing them into various themes.

Keywords: advertising, brands, fashion, graphic design, luxury, semiotic analysis, semiology, visual analysis, visual communication

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

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A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

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The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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Authors: Nabila Dwi Agustin, Ria Septitis Mentari, Nugroho Adi Sasongko

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Indonesia is experiencing a crisis in the development of defense equipment. Most of Indonesia's defense equipment must import its parts from other countries. Moreover, the area of Indonesia is 2/3 of its territory is the sea areas. For the protection of marine areas, Indonesia relies solely on submarines in monitoring conditions and whether or not intruders enter their territory. In fact, we know the submarine has a large size so that the expenses are getting bigger, the time it takes longer and needs a big maneuver to operate the submarine. Indeed, the submarine can only be operated for deeper seas. Many other countries enter the underwater world of Indonesia but Indonesia could not do anything due to the limitations of underwater monitoring system. At the same time, reconnaissance and monitor for shallow seas cannot be done by submarine. Equipment that can be used for surveillance of shallow underwater areas shall be made. This study reviewed the current research and development initiative of the submarine unmanned vehicle (SUV) or unmanned undersea vehicle (UUV) in Indonesia. This can explore underwater without the need for an operator to operate in it, but we can monitor it from a long distance. UUV has several advantages that size can be reduced as we desired, rechargeable ship batteries, has a detection sonar commonly found on a submarine and agile movement to detect at shallow sea depth. In the sonar sensors consisted of MEMS (Micro Electro Mechanical System), the sonar system runs more efficiently and effectively to monitor the target. UUV that has been developed will be very useful if the equipment is used around the outlying islands and outer from Indonesia especially the island frequented by foreign submarines without us know. The impact of this may not be felt now but it will allow foreign countries to attack Indonesia from within for the future. In addition, UUV needs to be equipped with a anti-radar system so that submarines of other countries crossing borders cannot detect it and Indonesia anti-submarine vessels can take further security measures. As the recommendation, Indonesia should take decisive steps in the state border rules, especially submarines of other countries that deliberately cross the borders of the state. This decisive action not only by word alone but also action as well. Indonesia government should show the strength and sovereignty as the entire society unites and applies the principle of universal peace.

Keywords: submarine unmanned vehicle, submarine, development of defense equipment, the border of Indonesia

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

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Authors: Thomas Nally, Jane Ireland, Roxanne Khan, Philip Birch

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Intimate Partner Violence (IPV), a significant societal problem, affects individuals worldwide. However, the strategies victims use to keep safe are under-researched. IPV is significantly under-reported, and services often are not able to be accessed by all victims. Thus they are likely to use their own strategies to manage their victimization before being able to seek support. Two studies were completed to understand these strategies. A systematic review of the literature and study completed with professionals who work with victims was undertaken to understand this area. In study one, a systematic review of the literature (n=61 papers), were analyzed using Thematic Analysis. The results indicated that victims use a large array of behaviors to increase their sense of safety and coping with emotions but also experience significant barriers to help-seeking. In study 2, sixty-nine professionals completed a measure exploring the likelihood and effectiveness of various victim strategies regarding increasing their sense of safety. Strategies included in the measure were obtained from those identified in study 1. Findings indicated that professionals perceived victims of IPV to be more likely to employ safety strategies and coping behaviors that may be ineffective but not help-seeking behaviors. Further, the responses were analyzed using Cluster Analysis. Safety strategies resulted in five clusters; perpetrator-directed strategies, prevention strategies, cognitive reappraisal, safety planning and avoidance strategies. Help-Seeking resulted in six clusters; information or practical support, abuse-related support, emotional support, secondary support and informal support. Finally, coping resulted in four clusters; emotional coping, self-directed coping, thought recording/change and cognitive coping. Both studies indicate that victims may use a variety of strategies to manage their safety besides seeking help. Professionals working with victims, using a strength-based approach, should understand what is used and is effective for victims who are unable to leave the relationships or access external support.

Keywords: intimate partner violence, help-seeking, professional support, victims, victim coping, victim safety

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Authors: Marwan Jarrah, Nadia Nugrush, Sukainah Ali, Areej Allawzi

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This research article investigates how illnesses (different types and severity) are expressed in Arabic discourse with a particular focus on input coming from Colloquial Jordanian Arabic (CJA). Drawing on a corpus of naturally occurring conversations, this article offers evidence that illnesses are predominantly expressed through two different sets of expressive strategies, namely direct expressive strategies (DES) and indirect expressive strategies (IES). The latter are exclusively used when cancer and mental health disorders are targeted. IES include the substitution of the name of the illness with some religious expressions (e.g., ʔallah ʔijdʒi:rna ‘May Allah keeps us safe’) or certain terms especially when cancer is meant (e.g., haðˤa:k ʔil-maraðˤ ‘that disease’). On the other hand, DES are used in conjunction with other illnesses (e.g., heart, kidneys, diabetes, etc.), regardless of their severity. DES include specific formulas that remarkably mention the name of the inflicted organ (e.g., [with-SOMEONE the ORGAN] as in ʕinduh ʔil-qalb ‘lit. with-him the heart’ meaning ‘He has a heart disease). We discuss the effects of religious beliefs and local norms and values in determining the use of these strategies.

Keywords: Illnesses, pragmatics, expressive strategies, religion

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: V. A. Adzika, D. Ayim-Aboagye, T. Gordh

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Background and aims: Prevalence of Sickle Cell Disease (SCD) is high in Ghana but not much is known in terms of research into non-medical strategies for managing and coping with the pain associated with SCD. This study was carried out to examine effective non-medical related strategies patients use to cope and manage their SCD condition. Methods: SCD patients (387) consisting of 180 males and 204 females between 18-65 years old years participated in the study. A cross-sectional research design was used in which participants completed questionnaires on pain, non-medical coping and management strategies, anxiety, and depression. Results of multiple regression analysis showed that socio-demographic characteristics contributed to the variance in the pain associated with SCD. Results: Over 90% of participants reported that pains associated with SCD were the main reason for seeking treatment in SCD crisis. In terms of non-medical related coping strategies, attending a place of worship and praying were the main coping strategies used in SCD crises, suggesting that patients’ beliefs, particularly in a supernatural being, served as a mitigating factor in the process of coping with the pain associated with SCD crisis. Also, avoidance and withdrawal from people and social activities were reported to be strategies used to cope effectively with the pain associated with SCD crisis. Conclusion: This indicates that it is imperative to incorporate non-medical related coping and management strategies, especially religious beliefs and psychosocial factors, to coping and management of the pain associated with SCD.

Keywords: anxiety, depression, sickle cell disease, quality of life, socio-demographic characteristics, Ghana

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Authors: John E. Boberg, Steven J. Bourgeois

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The decline in student engagement and motivation through the middle years is well documented and clearly associated with a decline in mathematics achievement that persists through high school. To combat this trend and, very often, to meet high-stakes accountability standards, a growing number of parents, teachers, and schools have implemented various methods to incentivize learning. However, according to Self-Determination Theory, forms of incentivized learning such as public praise, tangible rewards, or threats of punishment tend to undermine intrinsic motivation and learning. By focusing on external forms of motivation that thwart autonomy in children, adults also potentially threaten relatedness measures such as trust and emotional engagement. Furthermore, these controlling motivational techniques tend to promote shallow forms of cognitive engagement at the expense of more effective deep processing strategies. Therefore, any short-term gains in apparent engagement or test scores are overshadowed by long-term diminished motivation, resulting in inauthentic approaches to learning and lower achievement. The current study focuses on the relationships between student trust, engagement, and motivation during these crucial years as students transition from elementary to middle school. In order to test the effects of controlled motivational techniques on achievement in mathematics, this quantitative study was conducted on a convenience sample of 22 elementary and middle schools from a single public charter school district in the south-central United States. The study employed multi-source data from students (N = 1,054), parents (N = 7,166), and teachers (N = 356), along with student achievement data and contextual campus variables. Cross-sectional questionnaires were used to measure the students’ self-regulated learning, emotional and cognitive engagement, and trust in teachers. Parents responded to a single item on incentivizing the academic performance of their child, and teachers responded to a series of questions about their acceptance of various incentive strategies. Structural equation modeling (SEM) was used to evaluate model fit and analyze the direct and indirect effects of the predictor variables on achievement. Although a student’s trust in teacher positively predicted both emotional and cognitive engagement, none of these three predictors accounted for any variance in achievement in mathematics. The parents’ use of incentives, on the other hand, predicted a student’s perception of his or her controlled motivation, and these two variables had significant negative effects on achievement. While controlled motivation had the greatest effects on achievement, parental incentives demonstrated both direct and indirect effects on achievement through the students’ self-reported controlled motivation. Comparing upper elementary student data with middle-school student data revealed that controlling forms of motivation may be taking their toll on student trust and engagement over time. While parental incentives positively predicted both cognitive and emotional engagement in the younger sub-group, such forms of controlling motivation negatively predicted both trust in teachers and emotional engagement in the middle-school sub-group. These findings support the claims, posited by Self-Determination Theory, about the dangers of incentivizing learning. Short-term gains belie the underlying damage to motivational processes that lead to decreased intrinsic motivation and achievement. Such practices also appear to thwart basic human needs such as relatedness.

Keywords: controlled motivation, student engagement, incentivized learning, mathematics achievement, self-determination theory, student trust

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Authors: Bushra Mussawar, Saleha Younus

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Students often view their academic life demanding and stressful. However, apart from academics, stress springs from various other sources namely, finance, family, health, friends etc. The present study aims to assess the level of perceived stress in medical and fine arts students, and to determine the coping strategies used by the students to mitigate stress. The sample of the study consisted of 178 medical and fine arts students. The sample was selected through purposive sampling. Pearson correlation coefficient and T-test were used to analyze data. Results of the study revealed that there exists a positive relationship between perceived stress and coping strategies. Additionally, the two groups showed marked differences in terms of stress perception and coping styles. The level of perceived stress was found to be high in medical students nonetheless, they employed more positive coping strategies than fine arts students who scored high on negative coping strategies which are deleterious to the overall wellbeing.

Keywords: perceived stress, coping strategies, medical, fine arts students

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Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Hui Zhang, Sherif Beskhyroun

Abstract:

Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Ahmed Usman Egye, Hamza Muhammad

Abstract:

Poverty alleviation is one of the most difficult challenges facing third world countries in their development efforts. Evidences in Nigeria showed that the number of those in poverty has continued to increase. This paper is aimed at analyzing the performance of poverty alleviation measures undertaken by successive administrations in Nigeria with a view to addressing the quagmire. The study identified the whole gamut of factors that served as stumbling blocks to the implementation of each of the strategies and recommended the involvement of local people in the identification and design of projects so that sufficient participation could be achieved.

Keywords: poverty, development, strategies, Nigeria

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Authors: Ying Zhou, Jian-Hua Wang

Abstract:

Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

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Authors: Warakorn Supwirapakorn

Abstract:

The purpose of this research was to study the effects of choice theory in group counseling on coping strategies of students. The sample consisted of 16 students at a boarding school, who had the lowest score on the coping strategies. The sample was divided into two groups by random assignment and then were assigned into the experimental group and the control group, with eight members each. The instruments were the Adolescent Coping Scale and choice theory group counseling program. The data collection procedure was divided into three phases: The pre-test, the post-test, and the follow-up. The data were analyzed by repeated measure analysis of variance: One between-subjects and one within-subjects. The results revealed that the interaction between the methods and the duration of the experiment was found statistically significant at 0.05 level. The students in the experimental group demonstrated significantly higher at 0.05 level on coping strategies score in both the post-test and the follow-up than in the pre-test and the control group. No significant difference was found on coping strategies during the post-test phase and the follow-up phase of the experimental group.

Keywords: coping strategies, choice theory, group counseling, boarding school

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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