Search results for: conflicts identification model

Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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Authors: Obinna Emmanuel Nkomadu

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Many illegal activities take place on the sea, including trafficking in arms, which constitutes one of the major threats to maritime security. Indeed, the dissemination of arms has hampered the peaceful settlement of many States in Africa, fuelled disputes into armed conflicts, and contributed to the prolongation of armed conflicts in many African States. The absence of international standards on the importation, exportation, and transfer of conventional arms is a contributory factor to conflict, displacement of people, crime, and terrorism on the continent of Africa, which in turn undermines peace, safety, security, stability, and sustainable development. South Africa and Nigeria have taken steps to address the illicit arms, but, despite those steps, arms trafficking at sea continues. To suppress the illicit arms and to combat a number of other threats to maritime security around the continent of Africa, the majority of AU members in 2016 adopted the African Charter on Maritime Security and Safety and Development in Africa (“the Lomé Charter”). However, the Lomé Charter is yet to come into force. This paper set out the pre-existing international legal instruments on arms to ascertain the domestic laws of South Africa and Nigeria relating to arms with the relevant provisions of the Charter in order to establish whether any legal steps are required to ensure that South Africa and Nigeria comply with its obligations under the Lomé Charter should it decide to ratify it. The legal steps include cooperating in establishing policies, as well as a regional and continental institution, and ensuring the implementation of such policies. The paper concludes ratifying the Lomé Charter is a step in the right direction in suppressing arms trafficking at sea, in addition to filling those gaps or limitations in their relevant legislation.

Keywords: cooperation against arms trafficking at sea, Lomé Charter, maritime security, Nigerian and South Africa legislation on arms

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Authors: John Hardy

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The expansion of special operations forces (SOF) in the twenty-first century is often discussed in terms of the size and disposition of SOF units. Research regarding the number SOF personnel, the equipment SOF units procure, and the variety of roles and mission that SOF fulfill in contemporary conflicts paints a fascinating picture of changing expectations for the use of force. A strong indicator of the changing nature of SOF in contemporary conflicts is the fusion of strike and intelligence functions in the SOF in many countries. What were once more distinct roles on the kind of battlefield generally associated with the concept of conventional warfare have become intermingled in the era of persistent conflict which SOF face. This study presents a historical analysis of the co-evolution of the intelligence and direct action functions carried out by SOF in counterterrorism, counterinsurgency, and training and mentoring missions between 2004 and 2016. The study focuses primarily on innovation in the US military and the diffusion of key concepts to US allies first, and then more broadly afterward. The findings show that there were three key phases of evolution throughout the period of study, each coinciding with a process of innovation and doctrinal adaptation. The first phase was characterized by the fusion of intelligence at the tactical and operational levels. The second phase was characterized by the industrial counterterrorism campaigns used by US SOF against irregular enemies in Iraq and Afghanistan. The third phase was characterized by increasing forward collection of actionable intelligence by SOF force elements in the course of direct action raids. The evolution of strike and intelligence functions in SOF operations between 2004 and 2016 was significantly influenced by reciprocity. Intelligence fusion led to more effective targeting, which then increased intelligence collection. Strike and intelligence functions were then enhanced by greater emphasis on intelligence exploitation during operations, which further increased the effectiveness of both strike and intelligence operations.

Keywords: counterinsurgency, counterterrorism, intelligence, irregular warfare, military operations, special operations forces

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Authors: Omer Livvarcin, Mary Kay Park, Michael Miles

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The current literature includes a few studies that mention the impact of relations between teams, the business environment, and experiences from previous projects. There is, however, limited research that treats the phenomenon of project atmosphere (PA) as a whole. This is especially true of research identifying parameters and sub-parameters, which allow project management (PM) teams to build a project culture that ultimately imbues project success. This study’s findings identify a number of key project atmosphere parameters and sub-parameters that affect project management success. One key parameter identified in the study is a cluster related to cultural concurrence, including artifacts such as policies and mores, values, perceptions, and assumptions. A second cluster centers on motivational concurrence, including such elements as project goals and team-member expectations, moods, morale, motivation, and organizational support. A third parameter cluster relates to experiential concurrence, with a focus on project and organizational memory, previous internal PM experience, and external environmental PM history and experience). A final cluster of parameters is comprised of those falling in the area of relational concurrence, including inter/intragroup relationships, role conflicts, and trust. International and intercultural project management data was collected and analyzed from the following countries: Canada, China, Nigeria, South Korea and Turkey. The cross-cultural nature of the data set suggests increased confidence that the findings will be generalizable across cultures and thus applicable for future international project management success. The intent of the identification of project atmosphere as a critical project management element is that a clear understanding of the dynamics of its sub-parameters upon projects may significantly improve the odds of success of future international and intercultural projects.

Keywords: project management, project atmosphere, cultural concurrence, motivational concurrence, relational concurrence

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Thanh Nga Thai

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A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Adalberto Gregorio Back

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Historically, the Pinheiros River, which crosses the urban area of the largest South American metropolis, the city of São Paulo, has been the subject of several interventions involving different interests and multiple demands, including the implementation of road axes and industrial occupation in the city, following its floodplains. the dilution of sewers; generation of electricity, with the reversal of its waters to the Billings Dam; and urban drainage. These processes, together with the exclusionary and peripheral urban sprawl with high population density in the peripheries, result in difficulties for the collection and treatment of household sewage, which flow into the tributaries and the Pinheiros River itself. In the last 20 years, two separate projects have been undertaken to clean up its waters. The first one between 2001-2011 was the flotation system, aimed at cleaning the river in its own gutter with equipment installed near the Bilings Dam; and, more recently, from 2019 to 2022, the proposal to connect about 74 thousand dwellings to the sewage collection and treatment system, as well as to install treatment plants in the tributaries of Pinheiros where the connection to the system is impracticable, given the irregular occupations. The purpose of this paper is to make a comparative analysis on the dynamics of conflicts, interests and opportunities of coalitions between the actors involved in the two referred projects of pollution of the Pinheiros River. For this, we use the analysis of documents produced by the state government; as well as documents related to the legal disputes that occurred in the first attempt of decontamination involving the sanitation company; the Billings Dam management company interested in power generation; the city hall and regular and irregular dwellings not linked to the sanitation system.

Keywords: depollution of the Pinheiros River, interests groups, São Paulo, water energy nexus

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Authors: H. Gholami, M. Jalali Azizpour

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Stress Corrosion Crack (SCC) in pipeline is a type of environmentally assisted cracking (EAC), since its discovery in 1965 as a possible cause of failure in pipeline, SCC has caused, on average, one of two failures per year in the U.S, According to the NACE SCC DA a pipe line segment is considered susceptible to SCC if all of the following factors are met: The operating stress exceeds 60% of specified minimum yield strength (SMYS), the operating temperature exceeds 38°C, the segment is less than 32 km downstream from a compressor station, the age of the pipeline is greater than 10 years and the coating type is other than Fusion Bonded Epoxy(FBE). In this paper as a practical experience in NISOC, Direct Assessment (DA) Method is used for identification SCC defect in unpiggable pipeline located downstream of compressor station.

Keywords: stress corrosion crack, direct assessment, disbondment, transgranular SCC, compressor station

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

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Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Andre C Jordaan

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The end of the Cold War and rivalry between super powers has changed the nature of military build-up in many countries. A call from international institutions like the United Nations, International Monetary Fund and the World Bank to reduce the levels of military expenditure was the order of the day. However, this bid to cut military expenditure has not been forthright. Recently, active armed conflicts occurred in at least 46 states in 2021 with 8 in the Americas, 9 in Asia and Oceania, 3 in Europe, 8 in the Middle East and North Africa and 18 in sub-Saharan Africa. Global military expenditure in 2022 was estimated to be US$2,2 trillion, representing 2.2 per cent of global gross domestic product. Particularly sharp rises in military spending have followed in African countries and the Middle East. Global military expenditure currently follows two divergent trends, either a declining trend in the West caused mainly by austerity, efforts to control budget deficits and the wrapping up of prolonged wars. However, some parts of the world shows an increasing trend on the back of security concerns, geopolitical ambitions and some internal political factors. Conflict related fatalities in sub-Saharan Africa alone increased by 19 per cent between 2020 and 2021. The interaction between military expenditure (read conflict) and international trade is generally the cause of much debate. Some argue that countries’ fear of losing trade opportunities causes political decision makers to refrain from engaging in conflict when important trading partners are involved. However, three main arguments are always present when discussing the relationship between military expenditure or conflicts and international trade: Free trade could promote peaceful cooperation, it could trigger tension between trading blocs and partners, and trade could have no effect because conflict is based on issues that are more important. Military expenditure remains an important element of the overall government expenditure in many African countries. On the other hand, numerous researchers perceive increased international trade to be one of the main factors promoting economic growth in these countries. The purpose of this paper is therefore to determine what effect, if any, exist between the level of military expenditure and international trade within a selection of 19 African countries. Applying an augmented gravity model to explore the relationship between military expenditure and international trade, evidence is found to confirm the existence of an inverse relationship between these two variables. It seems that the results are in line with the Liberal school of thought where trade is seen as an instrument of conflict prevention. Trade is therefore perceived as a symptom of peace and not a cause thereof. In general, conflict or rumors of conflict tend to reduce trade. If conflict did not impede trade, economic agents would be indifferent to risk. Many claim that trade brings peace, however, it seems that it is rather peace that brings trade. From the results, it appears that trade reduces the risk of conflict and that conflict reduces trade.

Keywords: African countries, conflict, international trade, military expenditure

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Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

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Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Ngwako Daniel Sebola

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Introductory Statement: Religions are necessary as they offer and teach something to their adherence. People in one religion may not have a complete understanding of the Supreme Being (Deity) in a certain religion other than their own. South Africa, like other countries in the world, consists of various religions, including Christianity. Almost 80% of South African population adheres to the Christian faith, though in different denominations and sects. Each church fulfils spiritual needs that perhaps others cannot fill. African Independent Churches is one of the denominations in the country. These churches arose as a protest to the Western forms and expressions of Christianity. Their major concern was to develop an indigenous expression of Christianity. The relevance of African Independent Churches includes addressing the needs of the people holistically. Controlling diseases was an important aspect of change in different historical periods. Through healing services, leaders of African churches are able to attract many followers. The healing power associated with the founders of many African Initiated Churches leads to people following and respecting them as true leaders within many African communities. Despite its strong points, African Independent Churches, like many others, face a variety of challenges, especially conflicts. Ironically, destructive conflicts resulted in violence.. Such violence demonstrates a lack of informed religious orientation among those concerned. This paper investigates and analyses the causes of conflict and violence in the African Independent Church. The researcher used the Shembe and International Pentecostal Holiness Churches, in South Africa, as a point of departure. As a solution to curb violence, the researcher suggests useful strategies in handling conflicts. Methodology: Comparative and qualitative approaches have been used as methods of collecting data in this research. The intention is to analyse the similarities and differences of violence among members of the Shembe and International Pentecostal Holiness Churches. Equally important, the researcher aims to obtain data through interviews, questionnaires, focus groups, among others. The researcher aims to interview fifteen individuals from both churches. Finding: Leadership squabbles and power struggle appear to be the main contributing factors of violence in many Independent Churches. Ironically, violence resulted in the loss of life and destruction of properties, like in the case of the Shembe and International Pentecostal Holiness Churches. Violence is an indication that congregations and some leaders have not been properly equipped to deal with conflict. Concluding Statement: Conflict is a common part of every human existence in any given community. The concern is when such conflict becomes contagious; it leads to violence. There is a need to understand consciously and objectively towards devising the appropriate measures to handle the conflict. Conflict management calls for emotional maturity, self-control, empathy, patience, tolerance and informed religious orientation.

Keywords: African, church, religion, violence

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: Nadhia Maharany Siara, Muammal, Ilham Nurhakim, Rofifah Yusadi, M. Adie Putra Tanggara, I. Nyoman Suluh Wijaya

Abstract:

Urbanization in urban areas has impact to the demand of land use for housing, and it began to occur development in the high-density area called Kampung Kota. Kampung Kota grows and develops without planning or organically. The existence of Kampung Kota, becoming identity of the city development in Indonesia, gives self-identity to the city planning in Indonesia, but the existence of Kampung Kota in the development of the city in Indonesia is often considered as a source of environment, health, and social problems. This cause negative perception about the sustainability of Kampung Kota. This research aims to identify morphology and sustainability level of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City. So far, there have not been many studies that define sustainability of Kampung Kota especially from the perspective of Kampung Kota morphology as a part of urban housing areas. This research took place in in Polehan Sub-District, Blimbing District, Malang City which is one of the oldest Kampung Kota in Malang City. Identification of the sustainability level in this research is done by defining the morphology of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City with a descriptive approach to the observation case (Kampung Kota Polehan Sub-District). After that, definition of sustainability level is defined by quantifying the spatial structure by using the criteria from the new urbanism model which consist of buildings and populations density, compactness, diversity and mix land uses and sustainable transportation. In this case, the use of new urbanism model approach is very appropriate. New Urbanism is a design-driven strategy that is based on traditional forms to minimize urban sprawl in the suburbs. The result obtained from this study is the hometown of the level of sustainability in Polehan Sub-District, Blimbing District, Malang City of 3.2 and can be considered to have a good sustainability.

Keywords: Kampung Kota, new urbanism model, sustainability, urban morphology

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Authors: Marjan Heidarzadeh

Abstract:

High quality and purity of DNA isolated from canned tuna is essential for species identification. In this study, the efficiency of five different methods for DNA extraction was compared. Method of national standard in Iran, the CTAB precipitation method, Wizard DNA Clean Up system, Nucleospin and GenomicPrep were employed. DNA was extracted from two different canned tuna in brine and oil of the same tuna species. Three samples of each type of product were analyzed with the different methods. The quantity and quality of DNA extracted was evaluated using the 260 nm absorbance and ratio A260/A280 by spectrophotometer picodrop. Results showed that the DNA extraction from canned tuna preserved in different liquid media could be optimized by employing a specific DNA extraction method in each case. Best results were obtained with CTAB method for canned tuna in oil and with Wizard method for canned tuna in brine.

Keywords: canned tuna PCR, DNA, DNA extraction methods, species identification

Procedia PDF Downloads 638