Search results for: deep deterministic policy gradient (DDPG)

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Fadhl Qutaish

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This paper examines the pharyngealization spread in one of the Yemeni Arabic dialects, namely, Ibbi Arabic (IA). It investigates how pharyngealized sounds spread their acoustic features onto the neighboring vowels and change their default features. This feature has been investigated quietly well in MSA but still has to be deeply studied in the different dialect of Arabic which will bring about a clearer picture of the similarities and the differences among these dialects and help in mapping them based on the way this feature is utilized. Though the studies are numerous, no one of them has illustrated how far in the multi-syllabic word the spread can be and whether it takes a steady or gradient manner. This study tries to fill this gap and give a satisfactory explanation of the pharyngealization spread in Ibbi Dialect. This study is the first step towards a larger investigation of the different dialects of Yemeni Arabic in the future. The data recorded are represented in minimal pairs in which the trigger (pharyngealized or the non-pharyngealized sound) is in the initial or final position of monosyllabic and multisyllabic words. A group of 24 words were divided into four groups and repeated three times by three subjects which will yield 216 tokens that are tested and analyzed. The subjects are three male speakers aged between 28 and 31 with no history of neurological, speaking or hearing problems. All of them are bilingual speakers of Arabic and English and native speakers of Ibbi-Dialect. Recordings were done in a sound-proof room and praat software was used for the analysis and coding of the trajectories of F1 and F2 for the low vowel /a/ to see the effect of pharyngealization on the formant trajectory within the same syllable and in other syllables of the same word by comparing the F1 and F2 formants to the non-pharyngealized environment. The results show that pharyngealization spread is gradient (progressively and regressively). The spread is reflected in the gradual raising of F1 as we move closer towards the trigger and the gradual lowering of F2 as well. The results of the F1 mean values in tri-syllabic words when the trigger is word initially show that there is a raise of 37.9 HZ in the first syllable, 26.8HZ in the second syllable and 14.2HZ in the third syllable. F2 mean values undergo a lowering of 239 HZ in the first syllable, 211.7 HZ in the second syllable and 176.5 in the third syllable. This gradual decrease in the difference of F2 values in the non-pharyngealized and pharyngealized context illustrates that the spread is gradient. A similar result was found when the trigger is word-final which proves that the spread is gradient (progressively and regressively.

Keywords: pharyngealization, Yemeni Arabic, Ibbi dialect, pharyngealization spread

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Authors: Lihong Wu, Raymond Young

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The ability to learn is one of the most critical skills in the information age. However, many students do not have a clear understanding of what learning is, what they are learning, and why they are learning. Many students study simply to pass rather than to learn something useful for their career and their life. They have a misconception about learning and a wrong attitude towards learning. This research explores student attitudes to study in management education and explores how to intercede to lead students from shallow to deeper modes of learning.

Keywords: knowledge, surface learning, deep learning, education

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Authors: Yong Zhang

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Light has proven to be useful in a wide range of biomedical applications such as fluorescence imaging, photoacoustic imaging, optogenetics, photodynamic therapy, photothermal therapy, and light controlled drug/gene delivery. Taking photodynamic therapy (PDT) as an example, PDT has been proven clinically effective in early lung cancer, bladder cancer, head, and neck cancer and is the primary treatment for skin cancer as well. However, clinical use of PDT is severely constrained by the low penetration depth of visible light through thick tissue, limiting its use to target regions only a few millimeters deep. One way to enhance the range is to use invisible near-infrared (NIR) light within the optical window (700–1100nm) for biological tissues, extending the depth up to 1cm with no observable damage to the intervening tissue. We have demonstrated use of NIR-to-visible upconversion fluorescent nanoparticles (UCNPs), emitting visible fluorescence when excited by a NIR light at 980nm, as a nanotransducer for PDT to convert deep tissue-penetrating NIR light to visible light suitable for activating photosensitizers. The unique optical properties of UCNPs enable the upconversion wavelength to be tuned and matched to the activation absorption wavelength of the photosensitizer. At depths beyond 1cm, however, tissue remains inaccessible to light even within the NIR window, and this critical depth limitation renders existing phototherapy ineffective against most deep-seated cancers. We have demonstrated some new treatment modalities for deep-seated cancers based on UCNP hydrogel implants and miniaturized, wirelessly powered optoelectronic devices for light delivery to deep tissues.

Keywords: upconversion, fluorescent, nanoparticle, bioimaging, photodynamic therapy

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Authors: Shreyas Jayasimha, Suneel Anand Sundharesan, Rohan Tigadi

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In the recent past, the United States of America and Russia were the only two dominant players in the field of space exploration and had a virtual monopoly in the field of space and technology. However, this has changed over the past few years. Many other nation states such as India, China, and the UK have made significant progress in this field. Amongst these nations, the growth and development of the Indian space program have been nothing short of a miracle. Starting recently, India has successfully launched a series of satellites including its much acclaimed Mangalyaan mission, which placed a satellite in Mars’ orbit. The fact that India was able to attain this feat in its attempt demonstrates the enormous growth potential and promise that the Indian space program holds for the coming years. However, unlike other space-faring nations, India does not have a comprehensive and consolidated space insurance policy. In this regard, it is pertinent to note that, the costs and risks involved in a administering a space program are enormous. Therefore, in the absence of a comprehensive space insurance policy, any losses from an unsuccessful will have to be borne by the state exchequer. Thus, in order to ensure that Indian space program continues on its upward trajectory, the Indian establishment should seriously consider formulating a comprehensive insurance policy. This paper intends to analyze the international best practices followed by other space-faring nations in relation to space insurance policy. Thereafter, the authors seek to examine the current regime in India relating to space insurance policy. Finally, the authors will conclude by providing a series of recommendations regarding the essential elements that should be part of any Indian space insurance policy regime.

Keywords: India, space insurance policy, space law, Indian space research organization

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Authors: Rohit Kapoor

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In this paper, an attempt is made to formulate 3-echelon repairable parts inventory system under (S-1, S) policy. This analytical model is the extension of an exact formulation of two - echelon repairable parts inventory system, already reported in the established literature. In the present paper, we try to formulate the total cost expression consisting of two components, viz., system investment cost and expected backorder cost.

Keywords: (S-1, S) inventory policy, multi-echelon inventory system, repairable parts

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: John Bosco Ngendakurio

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The key question this paper asks is, ‘how does the refugee encampment policy undermine refugees’ potentials and fail local economy in East African countries?’ It is important to develop a full understanding of the legacies of the encampment policy for refugees’ performances economically, socially, and politically. The negative impacts of the encampment policy include the lack of participation or access to opportunities outside the refugee camps such as employment, education, and local integration, unfair imprisonments and constant alienation of refugees, mental and physical health issues, just to name a few. Evidence suggests that refugee camps in East Africa have progressively become open detention centres due to their designs, their locations, and movement restrictions imposed on refugees. Such restrictions in a region that hosts millions of refugees do not only undermine refugees’ potentials, but it also hurts the local economy- host countries miss out in many ways. Outlining the negative impacts of the encampment policy will enable governments and relevant non-governmental actors, including policymakers, to re-consider this policy with the aim to improve refugees’ participation and contributions in the broader society, promote socially cohesive practices, and help millions of refugees gain independence and reach their potentials financially, socially and politically, finally and truly giving the voice to the voiceless. The encampment policy undermines the general human security in East Africa, and it is one of the migration practices showcasing East African governments’ lack of will to protect human rights, especially within the most vulnerable population groups such as refugees.

Keywords: migration policy, immigration, refugees, encampment, migration, integration, social cohesion

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Authors: Mrinal Saurabh Bhaskar, Rahul E Ravindranathan, Priyangana Borah

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Energy plays a key role and as a driving force for economic and social growth for any country. To manage the energy sources and its efficient utilization in different economic sectors, energy policy of a country is critical. The energy performance of a country is measured in Energy Intensity and India’s Energy Intensity due to several policies interventions has reduced from 0.53 toe/1000USD (2010) in the year 2000 to 0.38 toe/1000USD (2010) in the year 2014, which is about 28 per cent reduction. The Government of India has taken several initiates to manage their increasing energy demand and meet the climate change goals defined by them. The major policy milestones in India related to energy are (i) Enactment of Energy Conservation (EC) Act 2001 (ii) Establishment of Bureau of Energy Efficiency 2001 (iii) National Action Plan on Climate Change (iv) Launch of Demand Side Management schemes (v) Amendment of EC Act 2010 (vi) Launch of Perform Achieve and Trade scheme 2012. Through a critical review, this paper highlights the key energy policy interventions by India, its benefits and impact, challenges faced and efforts of the Government to overcome such challenges. Such take away would be helpful for other countries who are proposing to prepare or amend their energy policy for their different economic sectors.

Keywords: energy, efficiency, climate, policy

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Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

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The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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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: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Muftahu Jibirin Salihu, Hazri Jamil

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The persisting challenge of access and enrolment to higher education in commonwealth countries has been reported in several studies, including reports of the international organization such as World Bank, UNESCO among others however from the macro perspective. The overarching aim of this study is to examine alternative policy practices towards improving access to university education in Nigeria at meso level of policy practice from evidence base policy studies using one university as a case. The study adopted a qualitative approach to gain insightful understanding on the issue of the study employing a semi-structure interview and policy documents as the means for obtaining the data and other relevant information for the study. The participants of the study were purposively chosen which comprise of a number of individuals from the selected university and other related organization which responsible for the policies development and implementation of Nigerian higher education system. From the findings of the study, several initiatives have been taken at meso level to address this challenge including the introduction of the University Matriculation Program as an alternative route for enhancing to access to the university education. However, the study further provided a number of recommendations which aimed at improving access to university education such as improving the entry requirements, society orientation on university education and the issue of ranking of certificate among the Nigerian higher institutions of learning.

Keywords: policy practice, access, enrolment, university, education, Nigeria

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Authors: Jennifer Isabelle Rios Rendón, Ursula Sanchez, Dana Lee Baker

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Disability Policy in México has witnessed numerous changed throughout the years. Physical disabilities are more often recognized in Mexican culture. However, with an emerging focus on neurological disabilities or differences in individuals’ new policies are needed to serve better and understand the needs of these populations. The need to understand and communicate with local leaders is imperative, as the lens used to analyze autism has historically been from a Western school of thought. We are looking to comprehend the disability policy subsystem in México - specifically how autism is perceived, the language used to describe it, and how it ties to the cultural stigma of disabilities that exist in México. Therefore, to understand this, we seek to interview multiple policy leaders on their experience in autism and disability policy. The goal is to conduct qualitative research through interviews with local autism and disability leaders in México. This methodology aims to answer the questions of what language commonly and culturally is utilized in disability policy, the context of how autism is perceived in México, and in general, the lived experience of the disability policy leaders that take part in this effort in México. Local activists and policy leaders were initially found through an online search then collected using snowball sampling. The interviews were conducted through a series of pre-formulated questions that the policy leader answered via email or a phone conversation with the researchers. Acknowledging the importance of language and accessibility, the need for the content to be in both English and Spanish as well as auditory and visual is essential to take steps in the inclusion of a Neurodiverse group of leaders. This work is a demonstration of the framework of the investigation which hopes to create a more complete understanding of the policy and political culture around autism in México. Results of the project include new insight into the developing relationship between the President Andrés Manuel López Obrador’s administration, disability activists, and neurodiverse communities. The project contributes to denormalizing the legacy of white supremacy in autism related, historically rooted in the assumption that autism occurs predominantly in white communities.

Keywords: autism, disability leaders, disability policy, México, Neurodiversity

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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: Tejeet Singh, Harmanjit Singh

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Creep behavior of thick-walled functionally graded cylinder consisting of AlSiC and subjected to internal pressure and high temperature has been analyzed. The functional relationship between strain rate with stress can be described by the well-known threshold stress based creep law with a stress exponent of five. The effect of imposing non-linear particle gradient on the distribution of creep stresses in the thick-walled functionally graded composite cylinder has been investigated. The study revealed that for the assumed non-linear particle distribution, the radial stress decreases throughout the cylinder, whereas the tangential, axial and effective stresses have averaging effect. The strain rates in the functionally graded composite cylinder could be reduced to significant extent by employing non-linear gradient in the distribution of reinforcement.

Keywords: functionally graded material, pressure, steady state creep, thick-cylinder

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Authors: Hitendra Raj Joshi, Bipin Lamichhane

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Groundwater is the main source of water for the industries of Balaju Industrial District (BID) and the denizens of Balaju-Boratar area. The quantity of groundwater is in a fatal condition in the area than earlier days. Water levels in shallow wells have highly lowered and deep wells are not providing an adequate amount of water as before because of higher extraction rate than the recharge rate. The main recharge zone of the shallow aquifer lies at the foot of Nagarjuna mountain, where recent colluvial debris are accumulated. Urbanization in the area is the main reason for decreasing water table. Recharge source for the deep aquifer in the region is aquiclude leakage. Sand layer above the Kalimati clay is the shallow aquifer zone, which is limited only in Balaju and eastern part of the Boratar, while the layer below the Kalimati clay spreading around Gongabu, Machhapohari, and Balaju area is considered as a potential area of deep aquifer. Over extraction of groundwater without considering water balance in the aquifers may dry out the source and can initiate the land subsidence problem. Hence, all the responsible of the industries in BID area and the denizens of Balaju-Boratar area should be encouraged to practice artificial groundwater recharge.

Keywords: aquiclude leakage, Kalimati clay, groundwater recharge

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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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: Margarita Grushanina

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After several prominent central banks including European Central Bank (ECB), Federal Reserve System (Fed), Bank of Japan and Bank of England employed unconventional monetary policies in the aftermath of the financial crisis of 2008-2009 the problem of identification of the effects from such policies became of great interest. One of the main difficulties in identification of shocks from unconventional monetary policy measures in structural VAR analysis is that they often are anticipated, which leads to a non-fundamental MA representation of the VAR model. Moreover, the unconventional monetary policy actions may indirectly transmit to markets information about the future stance of the interest rate, which raises a question of the plausibility of the assumption of orthogonality between shocks from unconventional and conventional policy measures. This paper offers a method of identification that takes into account the abovementioned issues. The author uses factor-augmented VARs to increase the information set and identification through heteroskedasticity of error terms and rank restrictions on the errors’ second moments’ matrix to deal with the cross-correlation of the structural shocks.

Keywords: factor-augmented VARs, identification through heteroskedasticity, monetary policy, structural VARs

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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: Diego Moya, Juan Paredes, Clay Aldas, Ramiro Tite, Prasad Kaparaju

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Globally, energy policy for geothermal development is addressed in different forms, depending on the economy, resources, country-development, environment aspects and technology access. Although some countries have established strong regulations and standards for geothermal exploration, exploitation and sustainable use at the policy level (government departments and institutions), others have discussed geothermal laws at legal levels (congress – a national legislative body of a country). Appropriate regulations are needed not only to meet local and international funding requirements but also to avoid speculation in the use of the geothermal resource. In this regards, this paper presents the results of a systematic, qualitative and critical literature review of geothermal energy policy worldwide addressing two scenarios: policy and legal levels. At first, literature is collected and classified from scientific and government sources regarding geothermal energy policy of the most advanced geothermal producing countries, including Iceland, New Zealand, Mexico, the USA, Central America, Italy, Japan, Philippines, Indonesia, Kenia, and Australia. This is followed by a systematic review of the literature aiming to know the best geothermal practices and what remains uncertain regarding geothermal policy implementation. This analysis is made considering the stages of geothermal production. Furthermore, a qualitative analysis is conducted comparing the findings across geothermal policies in the countries mentioned above. Then, a critical review aims to identify significant items in the field to be applied in countries with geothermal potential but with no or weak geothermal policies. Finally, patterns and relationships are detected, and conclusions are drawn.

Keywords: assessment, geothermal, energy policy, worldwide

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Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah

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Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.

Keywords: image registration, mutual information, image gradients, image transformations

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Authors: Mohamed Chakroun

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In this paper, we analyze the macroeconomic impacts of Oman’s strategy to transition to a green economy by 2050. Our objective is to determine the most effective climate policy instrument to facilitate this transition. By utilizing a Dynamic Stochastic General Equilibrium (DSGE) model, we assess the effectiveness of three climate policy tools: a carbon tax, subsidies to green assets, and taxes on brown assets. Our results indicate that a combination of a carbon tax, along with differentiated taxes and subsidies on green and brown assets, proves to the most effective policy in reducing emissions while maintaining macroeconomic stability. The findings of this study demonstrate the need for policymakers to balance the immediate goals of reducing emissions with the economic costs involved. Implementing a gradual transition strategy may be preferable as it allows for mitigating the negative economic impacts while facilitating the shift towards a green economy.

Keywords: green economy, carbon tax, DSGE model, climate policy, sustainable growth

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Authors: S. Yakubu, E. A. Isah

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One of the objectives of the school discipline policy is to instill discipline among students. However, despite the availability of this policy in various secondary schools in Nigeria, there seem to be numerous cases of indiscipline among students, which has become a source of concern to all stakeholders in the education sector. In an attempt to proffer possible solutions to this unending challenge, the study investigated the influence of knowledge and attitude on compliance of secondary school students towards school discipline policy in Ibadan North Local Government Area of Oyo State, Nigeria. The descriptive survey research design was employed to collect the requisite data. The multi-stage sampling procedure was adopted to select 570 respondents as the sample for the study. The data collected were analyzed using statistical measures of Mean, Standard deviation and Pearson Product Moment Correlation. The findings of the study showed that knowledge and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State were significantly related (r =0.330, p<0.05). The study also revealed a significant relationship between attitude and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State (r = 0.593, p<0.05). Based on the findings, it was recommended that school rules and regulations should be emphasized and given more awareness for easy compliance. Also, students should be encouraged to portray a positive attitude towards their respective rules and regulations.

Keywords: knowledge, attitude, compliance, school discipline policy

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Authors: Chandra Mukherjee

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The prevalent knowledge of the biological systems is based on the standard scientific perception of natural equilibrium, determination and predictability. Recently, a rethinking of concepts was presented and a new scientific perspective emerged that involves complexity theory with deterministic chaos theory, nonlinear dynamics and theory of fractals. The unpredictability of the chaotic processes probably would change our understanding of diseases and their management. The mathematical definition of chaos is defined by deterministic behavior with irregular patterns that obey mathematical equations which are critically dependent on initial conditions. The chaos theory is the branch of sciences with an interest in nonlinear dynamics, fractals, bifurcations, periodic oscillations and complexity. Recently, the biomedical interest for this scientific field made these mathematical concepts available to medical researchers and practitioners. Any biological network system is considered to have a nominal state, which is recognized as a homeostatic state. In reality, the different physiological systems are not under normal conditions in a stable state of homeostatic balance, but they are in a dynamically stable state with a chaotic behavior and complexity. Biological systems like heart rhythm and brain electrical activity are dynamical systems that can be classified as chaotic systems with sensitive dependence on initial conditions. In biological systems, the state of a disease is characterized by a loss of the complexity and chaotic behavior, and by the presence of pathological periodicity and regulatory behavior. The failure or the collapse of nonlinear dynamics is an indication of disease rather than a characteristic of health.

Keywords: HRV, HRVI, LF, HF, DII

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Authors: Shuaibu Umar Abdul

Abstract:

This paper examines Nigeria’s foreign policy in the age of global terrorism. It worth saying that the threat of ‘terrorism’ is not peculiar to Western and Middle Eastern countries alone, its tentacles are now spreading all over, Africa inclusive. The issue of domestic terrorism in Nigeria has become pervasive since the return of democratic rule in 1999. This development has never been a witness in any form throughout the year of statehood in Nigeria, the issues of banditry, armed robbery, ritual killing, and criminal activities like kidnapping and pipeline vandalization, the breakdown of law and order, poorly managed infrastructural facilities and corruption remain synonymous to Nigeria. These acts of terrorism no doubt have constituted a challenge that necessitates the paradigm shift in Nigeria’s foreign policy. The study employed the conceptual framework of analysis to lead interrogation; secondary sources were used to generate data while descriptive and content analysis were considered for data presentation and interpretation. In view of the interrogation and discussion on the subject matter, the paper revealed that Nigerian government underrated and underestimated the strength of terrorism within and outside her policy hence, it becomes difficult to address. As a response to the findings and conclusion of the study, the paper recommends among others that Nigeria’s foreign policy has to be rethought, reshaped and remodeled in cognizance to the rising global terrorism for peace, growth and development in the country.

Keywords: foreign policy, globe, Nigeria, rethinking, terrorism

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Authors: Amneh Alkurdi, Yasean Tahat, Hamzeh Almuali

Abstract:

Purpose: The primary objective of the present paper is to examine the impact of CG attributes, including the board size, independency, separation and managerial ownership) on firm dividend payouts policy; using a sample of 72 Jordanian listed companies for the period of 2007-2013. Methodology: The study does manually review the sample firm’s annual reports for data collection and use OLS regression to carry out this investigation. Findings: The findings indicate that CG attributes have a strong impact on dividend payouts policy. In particular, board size, independency and separation have had significant associations with dividends payouts indicating that such variables matter when determining on dividends which may mitigate the conflicts between stakeholders’ and managers’ interests. The results also indicate that managerial ownership has had no significant impact on the dividends policy suggesting that managers do not use the strength of their position to influence the dividends policy. Finally, the results show that firm size and profitability have had statistically positive associations with dividend payouts, while this was not the case for firm leverage and growth where significant and positive relationships were documented. Originality/implication: The current paper extends the extant literature in this field by investigating the impact of the board composition on dividends and provides some insights for policy makers in emerging markets.

Keywords: corporate governance, dividends payouts policy, jordan, accounting

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Authors: Nino Grigolaia

Abstract:

Introduction - The paper discusses the role of industrial policy in the development of the economy in the country. The main challenges on the way to the implementation of industrial policy are analyzed: the long-term period of industrial policy, the risk of changes in priorities, the limited scope and external shocks. Methodology - Various research methods are used in the paper. The methods of induction, deduction, analysis, synthesis, analogy, correlation and statistical observation are used. Main Findings - Based on the analysis of the current situation in Georgia, the obstacles to the country's industrialization and its supporting factors are identified. Also, the challenges of the country's core industrial policies are revealed. Specific industry development strategies, ways of state support and main directions of new industrial policies are identified. Conclusion - The paper concludes that the development of the industrial sector is critical for the future growth and development of the Georgian economy, which will accelerate the industrialization and structural transformation processes, reduce the trade deficit, increase the exports and create more jobs in the country. The listed changes will guarantee the improvement of the socio-economic situation of the population. Accordingly, it is revealed that the study of industrial policy in Georgia is still actual. Based on the analysis, relevant conclusions in the field of industrialization of the country are developed and recommendations are proposed.

Keywords: industrialization , industrial policy, industrialization of the economy, Georgia priorities

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