Search results for: regional vector

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

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Authors: Waseem Akram, Hafiz Azhar Ali Khan

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Unplanned urbanization together with change in life from simple to more technologically advanced style with flow of rural masses to urban areas has played a vital role in pilling loads of solid wastes in our environment. The cities and towns have expanded beyond boundaries. Even the uncontrolled population expansion has caused the overall environmental burden. Thus, today the indifference remains as one of the biggest trash that has come up due to the non-responsive behavior of the people. Everyday huge amount of solid waste is thrown in the streets, on the roads, parks, and in all those places that are frequently and often visited by the human beings. This behavior based response in many countries of the world has led to serious health concerns and environmental issues. Over 80% of our products that are sold in the market are packed in plastic bags. None of the bags are later recycled but simply become a permanent environment concern that flies, choke lines or are burnt and release toxic gases in the environment or form dumps of heaps. Lack of classification of the daily waste generated from houses and other places lead to worst clogging of the sewerage lines and formation of ponding areas which ultimately favor vector borne disease and sometimes become a cause of transmission of polio virus. Solid waste heaps were checked at different places of the cities. All of the wastes on visual assessments were classified into plastic bags, papers, broken plastic pots, clay pots, steel boxes, wrappers etc. All solid waste dumping sites in the cities and wastes that were thrown outside of the trash containers usually contained wrappers, plastic bags, and unconsumed food products. Insect populations seen in these sites included the house flies, bugs, cockroaches and mosquito larvae breeding in water filled wrappers, containers or plastic bags. The population of the mosquitoes, cockroaches and houseflies were relatively very high in dumping sites close to human population. This population has been associated with cases like dengue, malaria, dysentery, gastro and also to skin allergies during the monsoon and summer season. Thus, dumping of the huge amount of solid wastes in and near the residential areas results into serious environmental concerns, bad smell circulation, and health related issues. In some places, the same waste is burnt to get rid of mosquitoes through smoke which ultimately releases toxic material in the atmosphere. Therefore, a proper environmental strategy is needed to minimize environmental burden and promote concepts of recycled products and thus, reduce the disease burden.

Keywords: solid waste accumulation, disease burden, mosquitoes, vector borne diseases

Procedia PDF Downloads 278

Authors: Belachew Gebrewold

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The Horn of Africa is marred by complex and systematic internal and external political, economic and social-cultural causes of conflict that result in internal displacement and migration. This paper engages with them and shows how such a study can help us to understand migration, both in this region and more generally. The conflict has occurred within states, between states, among proxies, between armies. Human insecurities as a result of the state collapse of Somalia, the rise of Islamic fundamentalism in the whole region, recurrent drought affecting the livelihoods of subsistence farmers as well as nomads, exposure to hunger, environmental degradation, youth unemployment, rapid growth of slums around big cities, and political repression (especially in Eritrea) have been driving various segments of the regional population into regional and international migration. Eritrea has been going through a brutal dictatorship which pushes many Eritreans to flee their country and be exposed to human trafficking, torture, detention, and agony on their way to Europe mainly through Egypt, Libya and Israel. Similarly, Somalia has been devastated since 1991 by unending civil war, state collapse, and radical Islamists. There are some important aspects to highlight in the conflict-migration nexus in the Horn of Africa: first, the main push factor for the Somalis and Eritreans to leave their countries and risk their lives is the physical insecurity they have been facing in their countries. Secondly, as a result of the conflict the economic infrastructure is massively destroyed. Investment is rare; job opportunities are out of sight. Thirdly, in such a grim situation the politically and economically induced decision to migrate is a household decision, not only an individual decision. Based on this third point this research study took place in the Horn of Africa between 2014 and 2016 during different occasions. The main objective of the research was to understanding how the increasing migration is affecting the socio-economic and socio-political environment, and conversely how the socio-economic and socio-political environments are increasing migration decisions; and whether and how these decisions are individual or family decisions. The main finding is the higher the human insecurity, the higher the family decision; the lower the human insecurity, the higher the individual decision. These findings apply not only to the Eritrean, Somali migrants but also to Ethiopian migrants. But the general impacts of migration on sending countries’ human security is quite mixed and complex.

Keywords: Eritrea, Ethiopia, Horn of Africa, insecurity, migration, Somalia

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Authors: K. Bokreta, D. Benanaya

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The objective of this study is to examine the relative effectiveness of monetary and fiscal policy in Algeria using the econometric modelling techniques of cointegration and vector error correction modelling to analyse and draw policy inferences. The chosen variables of fiscal policy are government expenditure and net taxes on products, while the effect of monetary policy is presented by the inflation rate and the official exchange rate. From the results, we find that in the long-run, the impact of government expenditures is positive, while the effect of taxes is negative on growth. Additionally, we find that the inflation rate is found to have little effect on GDP per capita but the impact of the exchange rate is insignificant. We conclude that fiscal policy is more powerful then monetary policy in promoting economic growth in Algeria.

Keywords: economic growth, monetary policy, fiscal policy, VECM

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Authors: H. A. Alzomor, B. K. Ouda, A. M. Eldeib

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Successful regional anesthesia depends upon precise location of the peripheral nerve or nerve plexus. Locating peripheral nerves is preferred to be done using nerve stimulation. In order to generate a nerve impulse by electrical means, a minimum threshold stimulus of current “rheobase” must be applied to the nerve. The technique depends on stimulating muscular twitching at a close distance to the nerve without actually touching it. Success rate of this operation depends on the accuracy of current intensity pulses used for stimulation. In this paper, we will discuss a circuit and algorithm for closed loop control for the current, theoretical analysis and test results and compare them with previous techniques.

Keywords: Close Loop Control (CLC), constant current, nerve locator, rheobase

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Authors: Fatemeh Nemati, Lucinda Leonard, Gwyn Lintern, Richard Thomson

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In this study, we will use modern numerical modeling approaches to estimate tsunami risks to the southern coast of British Columbia from landslides. Wave generation is to be simulated using the NHWAVE model, which solves the Navier-Stokes equations due to the more complex behavior of flow near the landslide source; far-field wave propagation will be simulated using the simpler model FUNWAVE_TVD with high-order Boussinesq-type wave equations, with a focus on the accurate simulation of wave propagation and regional- or coastal-scale inundation predictions.

Keywords: FUNWAVE-TVD, landslide-generated tsunami, NHWAVE, tsunami risk

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Mirka Januszkiewicz

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The Regional Municipality of Durham is the upper level of a two-tier municipal and regional structure comprised of eight lower-tier municipalities. With a population of 655,000 in both urban and rural settings, the Region is approximately 2,537 square kilometers neighboring the City of Toronto, Ontario Canada to the east. The Region has been focused on diverting waste from disposal since the development of its Long Term Waste Management Strategy Plan for 2000-2020. With a 54 percent solid waste diversion rate, the focus now is on achieving 70 percent diversion on the path to zero waste using local waste management options whenever feasible. The Region has an Integrated Waste Management System that consists of a weekly curbside collection of recyclable printed paper and packaging and source separated organics; a seasonal collection of leaf and yard waste; a bi-weekly collection of residual garbage; and twice annual collection of intact, sealed household batteries. The Region also maintains three Waste Management Facilities for residential drop-off of household hazardous waste, polystyrene, construction and demolition debris and electronics. Special collection events are scheduled in the spring, summer and fall months for reusable items, household hazardous waste, and electronics. The Region is in the final commissioning stages of an energy from the waste facility for residual waste disposal that will recover energy from non-recyclable wastes. This facility is state of the art and is equipped for installation of carbon capture technology in the future. Despite all of these diversion programs and efforts, there is still room for improvement. Recent residential waste studies revealed that over 50% of the residual waste placed at the curb that is destined for incineration could be recycled. To move towards a zero waste community, the Region is looking to more advanced technologies for extracting the maximum recycling value from residential waste. Plans are underway to develop a pre-sort facility to remove organics and recyclables from the residual waste stream, including the growing multi-residential sector. Organics would then be treated anaerobically to generate biogas and fertilizer products for beneficial use within the Region. This project could increase the Region’s diversion rate beyond 70 percent and enhance the Region’s climate change mitigation goals. Zero waste is an ambitious goal in a changing regulatory and economic environment. Decision makers must be willing to consider new and emerging technologies and embrace change to succeed.

Keywords: municipal waste, residential, waste diversion, zero waste

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: M. Bouferhane, A. Boukhebza, L. Hatab

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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

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Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: facebook, social media, credibility measurement, internet

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Authors: Zeynep Karaçor, Volkan Alptekin, Gökhan Akar, Tuba Akar

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This paper aims to review the phenomenon of triplet deficit which is called interaction of budget balance that make up the overall balance of the economy, investment savings balance and current accounts balance in terms of Turkey. In this paper, triplet deficit state in Turkish economy has been analyzed with vector autoregressive model and Granger causality test using data covering the period of 1980-2010. According to VAR results, increase in current accounts is perceived on public sector borrowing requirement. These two variables influence each other bilaterally. Therefore, current accounts increase public deficit, whereas public deficit increases current accounts. It is not possible to mention the existence of a short-term Granger causality between variables at issue.

Keywords: internal and external deficit, stability, triplet deficit, Turkey economy

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Authors: Reza Mokhtari Malek Abadi, Mohsen Saghaei, Fatemeh Iman

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This paper investigates the indices of a creative city in Isfahan. Its main aim is to evaluate quantitative status of the creative city indices in Isfahan city, analyze the dispersion and distribution of these indices in Isfahan city. Concerning these, this study tries to analyze the creative city indices in fifteen area of Isfahan through secondary data, questionnaire, TOPSIS model, Shannon entropy and SPSS. Based on this, the fifteen areas of Isfahan city have been ranked with 12 factors of creative city indices. The results of studies show that fifteen areas of Isfahan city are not equally benefiting from creative indices and there is much difference between the areas of Isfahan city.

Keywords: grading, creative city, creative city evaluation indicators, regional planning model

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Authors: N. R. Mohamad, H. Ono, H. Haroon, A. Salleh, N. M. Z. Hashim

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In this research, we have studied and analyzed the modulation of light and liquid crystal in HPDLCs using Finite Domain Time Difference (FDTD) method. HPDLCs are modeled as a mixture of polymer and liquid crystals (LCs) that categorized as an anisotropic medium. FDTD method is directly solves Maxwell’s equation with less approximation, so this method can analyze more flexible and general approach for the arbitrary anisotropic media. As the results from FDTD simulation, the highest diffraction efficiency occurred at ±19 degrees (Bragg angle) using p polarization incident beam to Bragg grating, Q > 10 when the pitch is 1µm. Therefore, the liquid crystal is assumed to be aligned parallel to the grating constant vector during these parameters.

Keywords: birefringence, diffraction efficiency, finite domain time difference, nematic liquid crystals

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become an undisputed player in the ecological transition throughout the next decades. The decarbonization potential offered by this energy vector provides various opportunities for the so-called “hard-to-abate” sectors, including industrial production of iron and steel, glass, refineries and the heavy-duty transport. In this regard, Italy, in the framework of decarbonization plans for the whole European Union, has been considering a wider use of hydrogen to provide an alternative to fossil fuels in hard-to-abate sectors. This work aims to assess and compare different options concerning the pathway to be followed in the development of the future Italian energy system in order to meet decarbonization targets as established by the Paris Agreement and by the European Green Deal, and to infer a techno-economic analysis of the required asset alternatives to be used in that perspective. To accomplish this objective, the Energy System Optimization Model TEMOA-Italy is used, based on the open-source platform TEMOA and developed at PoliTo as a tool to be used for technology assessment and energy scenario analysis. The adopted assessment strategy includes two different scenarios to be compared with a business-as-usual one, which considers the application of current policies in a time horizon up to 2050. The studied scenarios are based on the up-to-date hydrogen-related targets and planned investments included in the National Hydrogen Strategy and in the Italian National Recovery and Resilience Plan, with the purpose of providing a critical assessment of what they propose. One scenario imposes decarbonization objectives for the years 2030, 2040 and 2050, without any other specific target. The second one (inspired to the national objectives on the development of the sector) promotes the deployment of the hydrogen value-chain. These scenarios provide feedback about the applications hydrogen could have in the Italian energy system, including transport, industry and synfuels production. Furthermore, the decarbonization scenario where hydrogen production is not imposed, will make use of this energy vector as well, showing the necessity of its exploitation in order to meet pledged targets by 2050. The distance of the planned policies from the optimal conditions for the achievement of Italian objectives is be clarified, revealing possible improvements of various steps of the decarbonization pathway, which seems to have as a fundamental element Carbon Capture and Utilization technologies for its accomplishment. In line with the European Commission open science guidelines, the transparency and the robustness of the presented results is ensured by the adoption of the open-source open-data model such as the TEMOA-Italy.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Elaine Lima Da Fonseca, Eliomar Pereira Da Silva Filho

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The modeling of areas susceptible to soil loss by hydro erosive processes consists of a simplified instrument of reality with the purpose of predicting future behaviors from the observation and interaction of a set of geoenvironmental factors. The models of potential areas for soil loss will be obtained through binary logistic regression, artificial neural networks, and support vector machines. The choice of the municipality of Colorado do Oeste in the south of the western Amazon is due to soil degradation due to anthropogenic activities, such as agriculture, road construction, overgrazing, deforestation, and environmental and socioeconomic configurations. Initially, a soil erosion inventory map constructed through various field investigations will be designed, including the use of remotely piloted aircraft, orbital imagery, and the PLANAFLORO/RO database. 100 sampling units with the presence of erosion will be selected based on the assumptions indicated in the literature, and, to complement the dichotomous analysis, 100 units with no erosion will be randomly designated. The next step will be the selection of the predictive parameters that exert, jointly, directly, or indirectly, some influence on the mechanism of occurrence of soil erosion events. The chosen predictors are altitude, declivity, aspect or orientation of the slope, curvature of the slope, composite topographic index, flow power index, lineament density, normalized difference vegetation index, drainage density, lithology, soil type, erosivity, and ground surface temperature. After evaluating the relative contribution of each predictor variable, the erosion susceptibility model will be applied to the municipality of Colorado do Oeste - Rondônia through the SPSS Statistic 26 software. Evaluation of the model will occur through the determination of the values of the R² of Cox & Snell and the R² of Nagelkerke, Hosmer and Lemeshow Test, Log Likelihood Value, and Wald Test, in addition to analysis of the Confounding Matrix, ROC Curve and Accumulated Gain according to the model specification. The validation of the synthesis map resulting from both models of the potential risk of soil erosion will occur by means of Kappa indices, accuracy, and sensitivity, as well as by field verification of the classes of susceptibility to erosion using drone photogrammetry. Thus, it is expected to obtain the mapping of the following classes of susceptibility to erosion very low, low, moderate, very high, and high, which may constitute a screening tool to identify areas where more detailed investigations need to be carried out, applying more efficient social resources.

Keywords: modeling, susceptibility to erosion, artificial intelligence, Amazon

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Authors: Abdu Zakari, Sai’d Jibril, Adoum A. Omar

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The leaves of Combretum molle was selected on the basis of its uses in folk medicine as insecticides. The leave extracts of Combretum molle was tested against the larvae of Artemia salina, i.e. Brine Shrimp Lethality Test (BST), Culex quinquefasciatus Say (Filaria disease vector) i.e. Larvicidal Test, using crude ethanol, n-hexane, chloroform, ethyl acetate, and methanol extracts. The methanolic extract proved to be the most effective in inducing complete lethality at minimum doses both in the BST and the Larvicidal activity test. The LC50¬ values obtained are 24.85 µg/ml and 0.4µg/ml respectively. The bioactivity-guided column chromatography afforded the pure compound ACM–3. ACM-3 was not active in the BST with LC50 value >1000µg/ml, but was active in the Larvicidal activity test with LC50 value 4.0µg/ml. ACM-3 was proposed to have the structure I, (Cholesta-β-D-Glucopyranoside).

Keywords: toxicity, larvicidal, Combretum molle, Artemia salina, Culex quinquefasciatus Say.

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Authors: Boopen Seetanah, R. V. Sannassee, Sheereen Fauzel, Robin Nunkoo

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The bulk of research on the impact of research and development (R&D) has been carried out in developed economies where the intensity of R&D expenditure has been relatively high and stable for many years. However, there is a paucity of similar studies in developing countries. In this paper, we provide empirical estimates of the impact of R&D investment on economic growth in a developing African economy (Mauritius) where R&D expenditure intensity has been low initially, but rising, albeit moderately in recent years. Using a dynamic time series analysis over the period 1980 to 2014 in a Vector Autoregressive framework, R & D is shown to have a positive and significant effect on the economic progress of the island, although the impact is considerably less when compared to both other ingredients of growth and also to reported elasticities fromdeveloped economies . Interestingly, there is evidence of bicausality between R & D and growth. furthermore, R & D positively impacts on both domestic and foreign investment, suggesting the possibilities of indirect effects.

Keywords: R & D, VECM, Africa, Mauritius

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Heather Fulford, Melanie Liddell

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The recruitment and retention of high quality employees can prove to be challenging for social enterprises, particularly in some of the core business support functions such as marketing, communications, IT and finance. This holds true for social enterprises in urban contexts, where roles with more attractive remuneration in these business functions can often be found quite readily in the private sector. For social enterprises situated in rural locations, the challenges of staff recruitment and retention are even more acute. Such challenges can lead to a skills deficit in rural social enterprises, which can, at best, hinder their growth potential, and worse, jeopardise their chances of survival. This in turn, can have a negative impact on the sustainability and resilience of the surrounding rural community in which the social enterprise is located. The purpose of this paper is to report on aspects of a collaborative initiative established to stimulate innovation and business growth in remote rural businesses in Scotland. Launched in 2010, this initiative was designed to attract young students and graduates from the region to stay in the region upon completion of their studies, and to attract others from outside the region to re-locate there post-university. To facilitate this, SMEs in the region were offered wage subsidies to encourage them to recruit a student or graduate on a work placement for up to one year to participate in an innovation or business growth-oriented project. A number of the employers offering work placements were social enterprises. Through analysis of the placement project and role specifications devised by the participating social enterprises, an overview is provided of their business development needs and the skills they require to stimulate innovation and growth. Scrutiny of the reflective accounts compiled by the students and graduates at the close of their work placements highlights the benefits they derived from being able to put their academic knowledge and skills into action within a social enterprise. Examination of interviews conducted with a sample of placement employers reveals the contribution the students and graduates made during the business development projects with the social enterprises. The challenges of hosting such placements are also discussed. The paper concludes with indications of the lessons learned and an outline of the wider implications for other remote rural locations in which social enterprises play an important role in the local economy and life of the community.

Keywords: resilience, rural development, regeneration, regional development, recruitment, resource management, retention, remuneration

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Authors: Yanchun Zuo, Yingao Liu, Wei Liu, Le Yu, Run Huang, Lixin Guo

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Electric field detection is important in many application scenarios. The traditional strategy is measuring the electric field with a man walking around in the area under test. This strategy cannot provide a satisfactory measurement accuracy. To solve the mentioned problem, an autopilot measurement system is divided. A mini-car is produced, which can travel in the area under test according to respect to the program within the CPU. The electric field measurement platform (EFMP) carries a central computer, two horn antennas, and a vector network analyzer. The mini-car stop at the sampling points according to the preset. When the car stops, the EFMP probes the electric field and stores data on the hard disk. After all the sampling points are traversed, an electric field map can be plotted. The proposed system can give an accurate field distribution description of the chamber.

Keywords: autopilot mini-car measurement system, electric field detection, field map, static zone measurement

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Authors: Louati Salma, Louhichi Awatef, Boujelbene Younes

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Analysis of the trade-off between competition and financial stability has been at the center of academic and policy debate for over two decades and especially since the 2007-2008 global financial crises. We use information on 10 OIC countries from 2005 to 2014 to investigate the influence of bank competition on individual bank stability and risk-taking. Alternatively, we explore whether the quality of prudential regulation may affect the nexus between competition and banking stability/risk-taking. We provide a particular attention to the Islamic banking system which principally involves with the Riba-free instruments as compared to the conventional interest-based system. We first run a dynamic panel regression (GMM), and then we apply a panel vector autoregressive (PVAR) methodology to compare both banking business models.

Keywords: Lerner index, Islamic banks, non-performing loans, prudential regulations, z-score

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Authors: Sun Jiaojiao, Fu Jiayan

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At present, in China, the research about the urban sustainability construction is still in the exploratory stage. The ecological problems of the coastal area are more sensitive and complicated. In the background of global warming with serious ecological damage, this paper deeply researches on the main characteristics of urban sustainability and measures how to build urban sustainability. Through combination with regional environmental and economic ability along the coastal area, we put forward the system planning framework, construction strategy and the evaluation index system in order to seek the way of building urban sustainability along coastal area in China.

Keywords: urban sustainability, coastal areas, construction strategy, evaluation index system

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Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Hasan Topacoglu

Abstract:

The Meiji Restoration was a chain of events that restored Japan in 1868 and considered as the beginning of Japanese Modernization by many scholars. In 1968, to honor its modern incarnation, Japan celebrated Meiji Centennial as one of the biggest Media Events in the country after the World War II. It was celebrated all around the country throughout the year following with a central event in Tokyo. Meanwhile, Japanese scholars started an opposition movement and claimed that Government was using this event to raise nationalism, pointing at Government’s statement on the meaning of Meiji. Most of the scholars, unfortunately, were hooked into the ideological problem of the Government’s way of planning and evaluated it as a failure. However, scholars missed out an important point that apart from the central event in Tokyo, each city planned its own event and celebrated it on a different date, also with a different theme. For example, Kyoto showed a regional characteristic and focused on Kyoto’s own culture, tradition etc., and highlighted a further past than 100 years. This was mainly because some areas/cities had a different ‘memory’ for Meiji Restoration than Tokyo which was reflected through the way they celebrated Meiji Centennial. On the other hand, 2023 will be the year of Turkish Republic Centennial. A year which will be marked by national and maybe even international events. Although an official committee has not been announced yet, The 2023 Vision, a list of goals has been released by the Government to coincide with the centenary of the Republic of Turkey in 2023 and there are some ongoing projects that are planned to be completed by then. By looking at the content of these projects, it is possible to say that Government is aiming to focus on Modernization through the Centennial. However, some of the projects are already showing some interesting characteristics such as the Istanbul New Airport whose design is inspired by Selimiye Mosque’s Islamic-Ottoman figure. It is true that Turkey and Japan have different historical backgrounds and the timeline of the Meiji Restoration and Foundation of Turkish Republic are different. Therefore, a particular comparison between these two events is not justified. However, they may have more in common than we are up to think because, each country marked the start of a new nation conceived on modern principles. For that reason, it is important to understand the similarities or differences between Meiji Centennial and Turkish Republic Centennial as a media event. This study introduces Meiji Centennial as a media event and analyses opposition movement along with the meaning of Meiji Centennial. Additionally, it explains regional characteristic differences and gives Kyoto as an example. Moreover, it introduces some of the ongoing Centennial projects in Turkey and analyses the meaning of the Turkish Republic Centennial through these projects. Without comparing Japan and Turkey, it explains the case of Japan but the discussion centers on deepening our understanding of Centennial as a Media Event and remarks some important aspects for Turkey’s upcoming Centennial events.

Keywords: media events, Meiji centennial, the 2023 vision, Turkish republic centennial

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

Abstract:

Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

Procedia PDF Downloads 173

Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

Abstract:

this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

Procedia PDF Downloads 292

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

Procedia PDF Downloads 150