Search results for: regional vector

Authors: Fongang Robert Tichuck

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This paper reports the findings of a study undertaken to assess the socio-economic and environmental impacts of mining in Bertoua Eastern Region of Cameroon. In addition to sampling community perceptions of mining activities, the study prescribes interventions that can assist in mitigating the negative impacts of mining. Marked environmental and interrelated socio-economic improvements can be achieved within regional artisanal gold mines if the government provides technical support to local operators, regulations are improved, and illegal mining activity is reduced.

Keywords: gold mining, socio-economic, mining activities, local people

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Authors: Naushad Mamode Khan

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The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood based estimating methodology. The joint generalized quasilikelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQLIII) that are based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: longitudinal, com-Poisson, ill-conditioned, INAR(1), GLMS, GQL

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Authors: Bryan Jenkins

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Introduction: The expansion of irrigation in the Canterbury region has led to the sustainability limits being reached for water availability and the cumulative effects of land use intensification. The institutional framework under New Zealand’s Resource Management Act was found to be an inadequate basis for managing water at sustainability limits. An alternative paradigm for water management was developed based on collaborative governance and nested adaptive systems. This led to the formulation and implementation of the Canterbury Water Management Strategy. Methods: The nested adaptive system approach was adopted. Sustainability issues were identified at multiple spatial and time scales and defined potential failure pathways for the water resource system. These included biophysical and socio-economic issues such as water availability, cumulative effects on water quality due to land use intensification, projected changes in climate, public health, institutional arrangements, economic outcomes and externalities, and, social effects of changing technology. This led to the derivation of sustainability strategies to address these failure pathways. The collaborative governance approach involved stakeholder participation and community engagement to decide on a regional strategy; regional and zone committees of community and rūnanga (Māori groups) members to develop implementation programmes for the strategy; and, farmer collectives for operational management. Findings: The strategy identified improvements in the efficiency of use of water already allocated was more effective in improving water availability than a reliance on increased storage alone. New forms of storage with less adverse impacts were introduced, such as managed aquifer recharge and off-river storage. Reductions of nutrients from land use intensification by improving management practices has been a priority. Solutions packages for addressing the degradation of vulnerable lakes and rivers have been prepared. Biodiversity enhancement projects have been initiated. Greater involvement of Māori has led to the incorporation of kaitiakitanga (resource stewardship) into implementation programmes. Emerging issues are the need for improved integration of surface water and groundwater interactions, increased use of modelling of water and financial outcomes to guide decision making, and, equity in allocation among existing users as well as between existing and future users. Conclusions: However, sustainability analysis indicates that the proposed levels of management interventions are not sufficient to achieve community targets for water management. There is a need for more proactive recovery and rehabilitation measures. Managing to environmental limits is not sufficient, rather managing adaptive cycles is needed. Better measurement and management of water use efficiency is required. Proposed implementation packages are not sufficient to deliver desired water quality outcomes. Greater attention to targets important to environmental and recreational interests is needed to maintain trust in the collaborative process. Implementation programmes don’t adequately address climate change adaptations and greenhouse gas mitigation. Affordability is a constraint on adaptive capacity of farmers and communities. More funding mechanisms are required to implement proactive measures. The legislative and institutional framework needs to be changed to incorporate water framework legislation, regional sustainability strategies and water infrastructure coordination.

Keywords: collaborative governance, irrigation management, nested adaptive systems, sustainable water management

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Authors: Ephraim Daka, Maxim Kotsemir

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The National system Innovation (NSI) have recently proliferated as a vehicle for addressing poverty and national competitiveness in the developing countries. While several governments in Sub-Saharan Africa have adopted the developed countries’ models of innovation to local conditions, the Zambian case is rather unique. This study highlights conceptual and socioeconomic challenges directed to the performances of the NSI. The paper analyses science and technology strategies with the inclusion of “innovation” and its effect towards improving socioeconomic elements. The authors reviewed STI policy and national strategy documents, followed by interviews compared to economical regional and national data sets. The NSI and its related to inter-linkages and support mechanism to socioeconomic development were explored.

Keywords: national system of innovation, socioeconomics, development, Zambia

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Authors: Alina Murtishcheva

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The development of an effective system of administrative supervision is a prerequisite for the functioning of local self-government on the basis of the rule of law. Administrative supervision of local self-government is of particular importance in the EU countries due to the influence of integration processes. The central authorities act on the international level; however, subnational authorities also have to implement European legislation in order to strengthen integration. Therefore, the central authority, being the connecting link between supranational and subnational authorities, should bear responsibility, including financial responsibility, for possible mistakes of subnational authorities. Consequently, the state should have sufficient mechanisms of control over local and regional authorities in order to correct their mistakes. At the same time, the control mechanisms do not deny the autonomy of local self-government. The paper analyses models of administrative supervision of local self-government in Ukraine, Poland, Lithuania, Belgium, Great Britain, Italy, and France. The research methods used in this paper are theoretical methods of analysis of scientific literature, constitutions, legal acts, Congress of Local and Regional Authorities of the Council of Europe reports, and constitutional court decisions, as well as comparative and logical analysis. The legislative basis of administrative supervision was scrutinized, and the models of administrative supervision were classified, including a priori control and ex-post control or their combination. The advantages and disadvantages of these models of administrative supervision are analysed. Compliance with Article 8 of the European Charter of Local Self-Government is of great importance for countries achieving common goals and sharing common values. However, countries under study have problems and, in some cases, demonstrate non-compliance with provisions of Article 8. Such non-conformity as the endorsement of a mayor by the Flemish Government in Belgium, supervision with a view to expediency in Great Britain, and the tendency to overuse supervisory power in Poland are analysed. On the basis of research, the tendencies of administrative supervision of local authorities’ activities in selected European countries are described. Several recommendations for Ukraine as a country that had been granted the EU candidate status are formulated. Having emphasised its willingness to become a member of the European community, Ukraine should not only follow the best European practices but also avoid the mistakes of countries that have long-term experience in developing the local self-government institution. This project has received funding from the Research Council of Lithuania (LMTLT), agreement № P-PD-22-194

Keywords: administrative supervision, decentralisation, legality, local authorities, local self-government

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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: Samuel Capintero, Ole H. Petersen

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This paper examines the utilization of public-private partnerships for the building and operation of wastewater treatment plants. Our research focuses on risk allocation in this kind of projects. Our analysis builds on more than hundred wastewater treatment plants built and operated through PPP projects in Aragon (Spain). The paper illustrates the consequences of an inadequate management of construction risk and an unsuitable transfer of demand risk in wastewater treatment plants. It also shows that the involvement of many public bodies at local, regional and national level further increases the complexity of this kind of projects and make time delays more likely.

Keywords: wastewater, treatment plants, PPP, construction

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Authors: Martha Lilia Del Rio Duque, Michelle Bonatti, Katharina Loehr, Marcos Lana, Tatiana Rodriguez, Stefan Sieber

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Nowadays, most agricultural practices can reduce the ability of ecosystems to provide goods and services. To enhance environmentally friendly food production and to maximize social and economic benefits, sustainable land use systems (SLUS) are one of the most critical strategies increasingly/strongly promoted by donors organizations, international agencies, and policymakers. This process involves the question of how SLUS can be scaled out also large-scale landscapes and not merely isolated experiments. As SLUS are context-specific strategies, diffusion and replication of successful SLUS in Colombia required the identification of main factors that facilitate this scaling out process. We applied a case study approach to investigate the scaling out process of SLUS in cocoa and livestock sector within peacebuilding territories in Colombia, specifically, in Cesar and Caqueta region. These two regions are contrasting, but both have a current trend of increasing land degradation. Presently in Colombia, Caqueta is one of the most deforested departments, and Cesar has some most degraded soils. Following a qualitative research approach, 19 semi-structured interviews and 2 focus groups were conducted with agroforestry experts in both regions to analyze (1) what does it mean a sustainable land use system in Cocoa/Livestock, specifically in Caqueta or Cesar and (2) to identify the key elements at the level of the following dimensions: biophysical, economic and profitability, market, social, policy and institutions that can explain how and why SLUS are replicated and spread among more producers. The Interviews were coded and analyzed using MAXQDA to identify, analyze and report patterns (themes) within data. As the results show, key themes, among which: premium market, solid regional markets and price stability, water availability and management, generational renewal, land use knowledge and diversification, producer organization and certifications are crucial to understand how the SLUS can have an impact across large-scale landscapes and how the scaling out process can be set up best in order to be successful across different contexts. The analysis further reveals which key factors might affect SLUS efficiency.

Keywords: agroforestry, cocoa sector, Colombia, livestock sector, sustainable land use system

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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

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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: Diep Thanh Tung

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This study aims to measure technical efficiency and examine productivity performance of livestock production in regions of Vietnam based on a panel data of 2008–2012. After four years, although there are improvements in efficiency of some regions, low technical efficiency, poor performance of productivity and its compositions are dominant features in almost regions. Households which much depend on livestock income in agricultural income or agricultural income in total income are more vulnerable than the others in term of livestock production.

Keywords: data envelopment analysis, meta-frontier, Malmquist, technical efficiency, livestock production

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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: Gonzalez Carlos, Martinez Fransisco

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There are various types of analysis that allow us to involve seismic phenomena that cause strong requirements for structures that are designed by society; one of them is a probabilistic analysis which works from prediction equations that have been created based on metadata seismic compiled in different regions. These equations form models that are used to describe the 5% damped pseudo spectra response for the various zones considering some easily known input parameters. The biggest problem for the creation of these models requires data with great robust statistics that support the results, and there are several places where this type of information is not available, for which the use of alternative methodologies helps to achieve adjustments to different models of seismic prediction.

Keywords: GMPM, 5% damped pseudo-response spectra, models of seismic prediction, PSHA

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Authors: Leyi Wang

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The effect of religion on conflicts is usually over-focused. Religion is not the root cause of conflicts. There are always social, political or economic factors pushing the acceleration of conflicts. Meanwhile, the charisma of religion on calling for adherents is often utilized by political leaders as a tool of providing legitimacy to the initiating of violence and mobilizing the public during conflicts. What people identify from the connections between religion and conflicts is fake. There are some strategies used by politicians to upgrade the conflicts into violence. Consequently, there are some assumptions of which try to limit the religion’s effects on accelerating conflicts. This essay aims to discuss the roles of religion in international relations and argues that the religion difference is not the real source of conflicts in the globe, by reviewing the relevant literature for understanding the research background and gap of this topic. Also, this essay will suggest some implementations on dealing with the regional conflicts.

Keywords: religion, conflicts, criticism, international relations

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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: 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: 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: 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: 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: 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: 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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 411

Authors: Mirka Januszkiewicz

Abstract:

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

Procedia PDF Downloads 206

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

Abstract:

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

Procedia PDF Downloads 102