Search results for: solid state reduction.

Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

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CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, Ontology Languages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

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Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: Wireless sensor network, node, application, monitoring, insecurity, environment.

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Authors: Osama Brinji, Wing Kong Chiu, Graham Tew

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Understanding the stability of rail ballast is one of the most important aspects in the railways. An unstable track may cause some issues such as unnecessary vibration and ultimately loss of track quality. The track foundation plays an important role in the stabilization of the railway. The dynamic response of rail ballast in the vicinity of the rail sleeper can affect the stability of the rail track and this has not been studied in detail. A review of literature showed that most of the works focused on the area under the concrete sleeper. Although there are some theories about the shear (longitudinal) effect of the rail ballast, these have not properly been studied and hence are not well understood. The stability of a rail track will depend on the compactness of the ballast in its vicinity. This paper will try to determine the dynamic response of the ballast to identify its resonant behaviour. This preliminary research is one of several studies that examine the vibration response of the granular materials. The main aim is to use this information for future design of sleepers to ensure that any dynamic response of the sleeper will not compromise the state of compactness of the ballast. This paper will report on the dependence of damping and the natural frequency of the ballast as a function of depth and distance from the point of excitation introduced through a concrete block. The concrete block is used to simulate a sleeper and the ballast is simulated with gravel. In spite of these approximations, the results presented in the paper will show an agreement with theories and the assumptions that are used in study the mechanical behaviour of the rail ballast.

Keywords: Ballast, dynamic response, sleeper, stability.

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.

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Authors: M. Chitsazi, B. Maraghechi, M. H. Rouhani

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Three-dimensional simulation of harmonic up generation in free electron laser amplifier operating simultaneously with a cold and relativistic electron beam is presented in steady-state regime where the slippage of the electromagnetic wave with respect to the electron beam is ignored. By using slowly varying envelope approximation and applying the source-dependent expansion to wave equations, electromagnetic fields are represented in terms of the Hermit Gaussian modes which are well suited for the planar wiggler configuration. The electron dynamics is described by the fully threedimensional Lorentz force equation in presence of the realistic planar magnetostatic wiggler and electromagnetic fields. A set of coupled nonlinear first-order differential equations is derived and solved numerically. The fundamental and third harmonic radiation of the beam is considered. In addition to uniform beam, prebunched electron beam has also been studied. For this effect of sinusoidal distribution of entry times for the electron beam on the evolution of radiation is compared with uniform distribution. It is shown that prebunching reduces the saturation length substantially. For efficiency enhancement the wiggler is set to decrease linearly when the radiation of the third harmonic saturates. The optimum starting point of tapering and the slope of radiation in the amplitude of wiggler are found by successive run of the code.

Keywords: Free electron laser, Prebunching, Undulator, Wiggler.

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Authors: D. Y. Bawa, M. I. Ribah, I. S. Jega, V. O. Oyedepo

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This study was conducted to determine the physicochemical characteristics and heavy metal concentration (Cadmium (Cd), Copper (Cu), Iron (Fe), Lead (Pb) and Zinc (Zn)) in freshwater from Jega river. 30 water samples were collected in two 1-liter sterile plastic containers from three designated sampling points, namely; Station A (before the bridge; upstream), Station B (at the bridge where human activities such as washing of cars, motorbike, clothes, bathing and other household materials are concentrated), Station C (after the bridge; downstream) fortnightly, between March and July 2014. Results indicated that the highest pH mean value of 7.08 ± 1.12 was observed in station C, the highest conductivity with the mean 58.75 ± 7.87 µs/cm was observed at station A, the highest mean value of the water total hardness was observed at station A (54 ± 16.11 mg/L), the highest mean value of nitrate deposit was observed in station A (1.66 ± 1.33 mg/L), the highest mean value of alkalinity was observed at station B (51.33 ± 6.66 mg/L) and the highest mean (39.56 ± 3.24 mg/L) of total dissolved solids was observed at station A. The highest concentration mean value of Fe was observed in station C (65.33 ± 4.50 mg/L), the highest concentrations of Cd was observed in station C (0.99 ± 0.36 mg/L), the mean value of 2.13 ± 1.99 mg/L was the highest concentration of Zn observed in station B, the concentration of Pb was not detected (ND) and the highest concentration of Cu with the mean value of 0.43 ± 0.16 mg/L was observed in station B, while the lowest concentration was observed at station C (0.27 ± 0.26 mg/L). Statistical analysis shows no significant difference (P > 0.05) among the sampling stations for both the physicochemical characteristics and heavy metal concentrations. The results were found to be within the internationally acceptable standard limits.

Keywords: Assessment, freshwater, heavy metal concentration, physicochemical.

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Authors: A. A. K. Abou-Arab, M. A. Abou Donia, Nevin E. Sharaf, Sherif R. Mohamed, A. K. Enab

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Lead being a toxic heavy metal that mankind is exposed to the highest levels of this metal from environmental pollutants. A total of 180 Male scalp hair samples were collected from different environments in Greater Cairo (GC), i.e. industrial, heavy traffic and rural areas (60 samples from each) having different activities during the period of, 1/5/2010 to 1/11/2012. Hair samples were collected during five stages. Data proved that the concentration of lead in male industrial areas of Cairo ranged between 6.2847 to 19.0432 μg/g, with mean value of 12.3288 μg/g. On the other hand, lead content of hair samples of residential-traffic areas ranged between 2.8634 to 16.3311 μg/g with mean value of 9.7552 μg/g. While lead concentration on the hair of the male residents living in rural area ranged between 1.0499-9.0402μg/g with mean value of 4.7327 μg/g. The Pb concentration in scalp hair of Cairo residents of residential-traffic and rural traffic areas was observed to follow the same pattern. The pattern was that of decrease concentration of summer and its increase in winter. Then, there was a marked increase in Pb concentration of summer 2012, and this increase was significant. These were obviously seen for the residential-traffic and rural areas residents. Pb pollution in residents of industrial areas showed the same seasonal pattern, but there was marked to decrease in Pb concentration of summer 2012, and this decrease was significant. Lead pollution in residents of GC was serious. It is worth noting that the atmosphere is still contaminated by lead despite a decade of using unleaded gasoline. Strong seasonal variation in higher Pb concentration on winter than in summer was found. Major contributions to the pollution with Pb could include industry emissions, motor vehicle emissions and long transported dust from outside Cairo. More attention should be paid to the reduction of Pb content of the urban aerosol and to the Pb pollution health.

Keywords: Hair, lead, environmental exposure, seasonal variations, Egypt.

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Authors: Nkechi Neboh, Josiah Adeyemo, Abimbola Enitan, Oludayo Olugbara

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Evolutionary Algorithms (EAs) have been used widely through evolution theory to discover acceptable solutions that corresponds to challenges such as natural resources management. EAs are also used to solve varied problems in the real world. EAs have been rapidly identified for its ease in handling multiple objective problems. Reservoir operations is a vital and researchable area which has been studied in the last few decades due to the limited nature of water resources that is found mostly in the semi-arid regions of the world. The state of some developing economy that depends on electricity for overall development through hydropower production, a renewable form of energy, is appalling due to water scarcity. This paper presents a review of the applications of evolutionary algorithms to reservoir operation for hydropower production. This review includes the discussion on areas such as genetic algorithm, differential evolution, and reservoir operation. It also identified the research gaps discovered in these areas. The results of this study will be an eye opener for researchers and decision makers to think deeply of the adverse effect of water scarcity and drought towards economic development of a nation. Hence, it becomes imperative to identify evolutionary algorithms that can address this issue which can hamper effective hydropower generation.

Keywords: Evolutionary algorithms, genetic algorithm, hydropower, multi-objective, reservoir operations.

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Authors: Solvita Kalnina, Tatjana Rakcejeva, Daiga Kunkulberga, Anda Linina

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Triticale is a manmade hybrid of wheat and rye that carries the A and B genome of durum wheat and the R genome of rye. In the scientific literature information about in Latvia harvested organic and conventional triticale grain physically-chemical composition was not found in general. Therefore, the main purpose of the current research was to investigate physically-chemical parameters of in Latvia harvested organic and convectional triticale grains. The research was accomplished on in Year 2012 from State Priekuli Plant Breeding Institute (Latvia) harvested organic and conventional triticale grains: “Dinaro”, “9403-97”, “9405-23” and “9402-3”. In the present research significant differences in chemical composition between organic and conventional triticale grains harvested in Latvia was found. It is necessary to mention that higher 1000 grain weight, bulk density and gluten index was obtained for conventional and organic triticale grain variety “9403-97”. However higher falling number, gluten and protein content was obtained for triticale grain variety “9405-23”.

Keywords: Physically-chemical parameters, technological properties, triticale grains.

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Authors: Dimitrios E. Kontaxis, George Litainas, Dimitrios P. Ptochos, Vaggelis P. Ptochos, Sotirios P. Ptochos, Dimitrios Beletsis, Konstantinos Kritikakis, Milan Sunaric

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Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination and sustainability of the supply chain procedures. The technology, the features and the characteristics of a complete, proprietary system, including hardware, firmware and software tools - developed in the context of a co-funded R&D program - are addressed and presented in this paper. 

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Kim H. K. Choy, Oliva H. K. Chu, W. Y. Keung, B. Lim, Winnie P. Y. Tang

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Background: The prevalence of workplace obesity is rising worldwide; therefore, the workplace is an ideal venue to implement weight control intervention. This pilot randomized controlled trial aimed to develop, implement, and evaluate a nutritional wellness program for obese health care providers working in a hospital. Methods: This hospital-based nutritional wellness program was an 8-week pilot randomized controlled trial for obese health care providers. The primary outcomes were body weight and body mass index (BMI). The secondary outcomes were serum fasting glucose, fasting cholesterol, triglyceride, high-density (HDL) and low-density (LDL) lipoprotein, body fat percentage, and body mass. Participants were randomly assigned to the intervention (n = 20) or control (n = 22) group. Participants in both groups received individual nutrition counselling and nutrition pamphlets, whereas only participants in the intervention group were given mobile phone text messages. Results: 42 participants completed the study. In comparison with the control group, the intervention group showed approximately 0.98 kg weight reduction after two months. Participants in intervention group also demonstrated clinically significant improvement in BMI, serum cholesterol level, and HDL level. There was no improvement of body fat percentage and body mass for both intervention and control groups. Conclusion: The nutritional wellness program for obese health care providers was feasible in hospital settings. Health care providers demonstrated short-term weight loss, decrease in serum fasting cholesterol level, and HDL level after completing the program.

Keywords: Health care provider, hospital, weight management, weight control.

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Authors: Bello Ali

Abstract:

The use of Information and Communication Technology (ICT) in tertiary institutions by lecturers and students has become a necessity for the enhancement of quality teaching and learning. This study examined availability, accessibility and utilization of ICT in Teaching-Learning Islamic Studies in Colleges of Education, North-East, Nigeria. The study adopted multi-stage sampling technique, in which, five out of the eleven Colleges of Education (both Federal and State owned) were purposively selected for the study. Primary data was drawn from the respondents by the use of questionnaire, interviews and observations. The results of the study, generally, indicate that the availability and accessibility to ICT facilities in Colleges of Education in North-East, Nigeria, especially in teaching/learning delivery of Islamic studies were relatively inadequate and rare to lecturers and students. The study further reveals that the respondents’ level of utilization of ICT is low and only few computer packages and internet services were involved in the ICT utilization, which is yet to reach the real expected situation of the globalization and advancement in the application of ICT if compared to other parts of the world, as far as the teaching and learning of Islamic studies is concerned. Observations and conclusion were drawn from the findings and finally, recommendations on how to improve on ICT availability, accessibility and utilization in teaching/ learning were suggested.

Keywords: Accessibility, availability, college of education, ICT, Islamic Studies, learning, North-Eastern, teaching, utilization.

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the point specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: Milling process, rotational speed, Artificial Neural Networks, temperature.

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Authors: Petr Cernohorsky, Jan Voracek

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Well-developed strategic marketing planning is the essential prerequisite for establishment of the right and unique competitive advantage. Typical market, however, is a heterogeneous and decentralized structure with natural involvement of individual or group subjectivity and irrationality. These features cannot be fully expressed with one-shot rigorous formal models based on, e.g. mathematics, statistics or empirical formulas. We present an innovative solution, extending the domain of agent based computational economics towards the concept of hybrid modeling in service provider and consumer market such as telecommunications. The behavior of the market is described by two classes of agents - consumer and service provider agents - whose internal dynamics are fundamentally different. Customers are rather free multi-state structures, adjusting behavior and preferences quickly in accordance with time and changing environment. Producers, on the contrary, are traditionally structured companies with comparable internal processes and specific managerial policies. Their business momentum is higher and immediate reaction possibilities limited. This limitation underlines importance of proper strategic planning as the main process advising managers in time whether to continue with more or less the same business or whether to consider the need for future structural changes that would ensure retention of existing customers or acquisition of new ones.

Keywords: Agent-based computational economics, hybrid modeling, strategic marketing, system dynamics.

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Authors: Vijay Shankar

Abstract:

Different techniques for estimating seasonal water use from soil profile water depletion frequently do not account for flux below the root zone. Shallow water table contribution to supply crop water use may be important in arid and semi-arid regions. Development of predictive root uptake models, under influence of shallow water table makes it possible for planners to incorporate interaction between water table and root zone into design of irrigation projects. A model for obtaining soil moisture depletion from root zone and water movement below it is discussed with the objective to determine impact of shallow water table on seasonal moisture depletion patterns under water table depth variation, up to the bottom of root zone. The role of different boundary conditions has also been considered. Three crops: Wheat (Triticum aestivum), Corn (Zea mays) and Potato (Solanum tuberosum), common in arid & semi-arid regions, are chosen for the study. Using experimentally obtained soil moisture depletion values for potential soil moisture conditions, moisture depletion patterns using a non linear root uptake model have been obtained for different water table depths. Comparative analysis of the moisture depletion patterns under these conditions show a wide difference in percent depletion from different layers of root zone particularly top and bottom layers with middle layers showing insignificant variation in moisture depletion values. Moisture depletion in top layer, when the water table rises to root zone increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato respectively. The paper also discusses the causes and consequences of increase in moisture depletion from top layers and exceptionally high reduction in bottom layer, and the possible remedies for the same. The numerical model developed for the study can be used to help formulating irrigation strategies for areas where shallow groundwater of questionable quality is an option for crop production.

Keywords: Moisture Depletion, crop root zone, ground water table, irrigation.

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Authors: Amin Kamal Akhnoukh, Lois Zaki Kamel, Magued Mourad Barsoum

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The objective of this research is to mitigate and prevent the alkali silica reactivity (ASR) in highway construction projects. ASR is a deleterious reaction initiated when the silica content of the aggregate reacts with alkali hydroxides in cement in the presence of relatively high moisture content. The ASR results in the formation of an expansive white colored gel-like material which forms the destructive tensile stresses inside hardened concrete. In this research, different types of local aggregates available in the State of Arkansas were mixed and mortar bars were poured according to the ASTM specifications. Mortar bars expansion was measured versus time and aggregates with potential ASR problems were detected. Different types of supplementary cementitious materials (SCMs) were used in remixing mortar bars with highly reactive aggregates. Length changes for remixed bars proved that different types of SCMs can be successfully used in reducing the expansive effect of ASR. SCMs percentage by weight is highly dependent on the SCM type. The result of this study will help avoiding future losses due to ASR cracking in construction project and reduce the maintenance, repair, and replacement budgets required for highways network.

Keywords: Alkali Silica Reaction, Aggregates, Moisture, Cracks, Mortar Bar Test supplementary cementitious materials.

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Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: Unmanned aerial vehicle, object tracking, deep learning, collision avoidance.

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Authors: Dávid Csercsik, Sándor Imre

Abstract:

The performance of state of the art worldwide telecommunication networks strongly depends on the efficiency of the applied routing mechanism. Game theoretical approaches to this problem offer new solutions. In this paper a new continuous network routing model is defined to describe data transfer in fixed telecommunication networks of multiple hosts. The nodes of the network correspond to routers whose latency is assumed to be traffic dependent. We propose that the whole traffic of the network can be decomposed to a finite number of tasks, which belong to various hosts. To describe the different latency-sensitivity, utility functions are defined for each task. The model is used to compare router and host intelligent types of routing methods, corresponding to various data transfer protocols. We analyze host intelligent routing as a transferable utility cooperative game with externalities. The main aim of the paper is to provide a framework in which the efficiency of various routing algorithms can be compared and the transferable utility game arising in the cooperative case can be analyzed.

Keywords: Routing, Telecommunication networks, Performance evaluation, Cooperative game theory, Partition function form games

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Authors: Jagadish H. Pujar, S. F. Kodad

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Recent developments in Soft computing techniques, power electronic switches and low-cost computational hardware have made it possible to design and implement sophisticated control strategies for sensorless speed control of AC motor drives. Such an attempt has been made in this work, for Sensorless Speed Control of Induction Motor (IM) by means of Direct Torque Fuzzy Control (DTFC), PI-type fuzzy speed regulator and MRAS speed estimator strategy, which is absolutely nonlinear in its nature. Direct torque control is known to produce quick and robust response in AC drive system. However, during steady state, torque, flux and current ripple occurs. So, the performance of conventional DTC with PI speed regulator can be improved by implementing fuzzy logic techniques. Certain important issues in design including the space vector modulated (SVM) 3-Ф voltage source inverter, DTFC design, generation of reference torque using PI-type fuzzy speed regulator and sensor less speed estimator have been resolved. The proposed scheme is validated through extensive numerical simulations on MATLAB. The simulated results indicate the sensor less speed control of IM with DTFC and PI-type fuzzy speed regulator provides satisfactory high dynamic and static performance compare to conventional DTC with PI speed regulator.

Keywords: Sensor-less Speed Estimator, Fuzzy Logic Control(FLC), SVM, DTC, DTFC, IM, fuzzy speed regulator.

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Authors: B. Tah, P. Pal, M. Mahato, R. Sarkar, G. B. Talapatra

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Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Keywords: Air/water interface, Catanionic micelle, Insulin, Langmuir-Blodgett film

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Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

Abstract:

Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: I. Laurence Aroquiaraj, K. Thangavel

Abstract:

Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.

Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.

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Authors: Md. Maksudur Rahman Khan, M. Rahim Uddin, Hamidah Abdullah, Kaykobad Md. Rezaul Karim, Abu Yousuf, Chin Kui Cheng, Huei Ruey Ong

Abstract:

A systematic study was conducted to explore the photocatalytic reduction of carbon dioxide (CO₂) into methanol on TiO₂ loaded copper ferrite (CuFe₂O₄) photocatalyst under visible light irradiation. The phases and crystallite size of the photocatalysts were characterized by X-ray diffraction (XRD) and it indicates CuFe₂O₄ as tetragonal phase incorporation with anatase TiO₂ in CuFe₂O₄/TiO₂ hetero-structure. The XRD results confirmed the formation of spinel type tetragonal CuFe₂O₄ phases along with predominantly anatase phase of TiO₂ in the CuFe₂O₄/TiO₂ hetero-structure. UV-Vis absorption spectrum suggested the formation of the hetero-junction with relatively lower band gap than that of TiO₂. Photoluminescence (PL) technique was used to study the electron–hole (e⁻/h⁺) recombination process. PL spectra analysis confirmed the slow-down of the recombination of electron–hole (e⁻/h⁺) pairs in the CuFe₂O₄/TiO₂ hetero-structure. The photocatalytic performance of CuFe₂O₄/TiO₂ was evaluated based on the methanol yield with varying amount of TiO₂ over CuFe₂O₄ (0.5:1, 1:1, and 2:1) and changing light intensity. The mechanism of the photocatalysis was proposed based on the fact that the predominant species of CO₂ in aqueous phase were dissolved CO₂ and HCO₃^- at pH ~5.9. It was evident that the CuFe₂O₄ could harvest the electrons under visible light irradiation, which could further be injected to the conduction band of TiO₂ to increase the life time of the electron and facilitating the reactions of CO₂ to methanol. The developed catalyst showed good recycle ability up to four cycles where the loss of activity was ~25%. Methanol was observed as the main product over CuFe₂O₄, but loading with TiO₂ remarkably increased the methanol yield. Methanol yield over CuFe₂O₄/TiO₂ was found to be about three times higher (651 μmol/g_cat L) than that of CuFe₂O₄ photocatalyst. This occurs because the energy of the band excited electrons lies above the redox potentials of the reaction products CO₂/CH₃OH.

Keywords: Photocatalysis, CuFe2O4/TiO2, band-gap energy, methanol.

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Authors: Patrick May Mukonki

Abstract:

KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: Mine planning, mine optimization, mine scheduling, SWOT analysis.

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Authors: S. Golmohammadi, M. Noorian Bidgoli

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Because the status and mechanical parameters of discontinuities in the rock mass are included in the calculations, various methods of rock engineering classification are often used as a starting point for the design of different types of structures. The Q-system is one of the most frequently used methods for stability analysis and determination of support systems of underground structures in rock, including tunnel. In this method, six main parameters of the rock mass, namely, the Rock Quality Designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water parameter (Jw) and Stress Reduction Factor (SRF) are required. In this regard, in order to achieve a reasonable and optimal design, identifying the effective parameters for the stability of the mentioned structures is one of the most important goals and the most necessary actions in rock engineering. Therefore, it is necessary to study the relationships between the parameters of a system and how they interact with each other and, ultimately, the whole system. In this research, it has been attempted to determine the most effective parameters (key parameters) from the six parameters of rock mass in the Q-system using the Rock Engineering System (RES) method to improve the relationships between the parameters in the calculation of the Q value. The RES system is, in fact, a method by which one can determine the degree of cause and effect of a system's parameters by making an interaction matrix. In this research, the geomechanical data collected from the water conveyor tunnel of Azad Dam were used to make the interaction matrix of the Q-system. For this purpose, instead of using the conventional methods that are always accompanied by defects such as uncertainty, the Q-system interaction matrix is coded using a technique that is actually a statistical analysis of the data and determining the correlation coefficient between them. So, the effect of each parameter on the system is evaluated with greater certainty. The results of this study show that the formed interaction matrix provides a reasonable estimate of the effective parameters in the Q-system. Among the six parameters of the Q-system, the SRF and Jr parameters have the maximum and minimum impact on the system, respectively, and also the RQD and Jw parameters have the maximum and minimum impact on the system, respectively. Therefore, by developing this method, we can obtain a more accurate relation to the rock mass classification by weighting the required parameters in the Q-system.

Keywords: Q-system, Rock Engineering System, statistical analysis, rock mass, tunnel.

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Authors: ZerarkaHizia, Akchiche Mustapha, Prunier Florent

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Landslide of Ain El Hammam (AEH) has been an old slip since 1969; it was reactivated after an intense rainfall period in 2008 where it presents a complex shape and affects broad areas. The schist of AEH is more or less altered; the alteration is facilitated by the fracturing of the rock in its upper part, the presence of flowing water as well as physical and chemical mechanisms of desegregation in joint of altered schist. The factors following these instabilities are mostly related to the geological formation, the hydro-climatic conditions and the topography of the region. The city of AEH is located on the top of a steep slope at 50 km from the city of TiziOuzou (Algeria). AEH’s topographic monitoring of unstable slope allows analyzing the structure and the different deformation mechanism and the gradual change in the geometry, the direction of change of slip. It also allows us to delimit the area affected by the movement. This work aims to study the behavior of AEH landslide with topographic monitoring and to validate the results with numerical modeling of the slip site, when the hydraulic factors are identified as the most important factors for the reactivation of this landslide. With the help of the numerical code PLAXIS 2D and PlaxFlow, the precipitations and the steady state flow are modeled. To identify the mechanism of deformation and to predict the spread of the AEH landslide numerically, we used the equivalent deviatory strain, and these results were visualized by MATLAB software.

Keywords: Equivalent deviatory strain, landslide, numerical modeling, topographic monitoring.

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Authors: Ruoya Huang, Ruoxian Huang, Edgar Huang

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Based on a convenience sample of 2,092 participants from across all 50 states of the United States, a survey was conducted to explore Americans’ mask-wearing behaviors during COVID-19 according to their political convictions, religious beliefs, and ethnic cultures from late July to early September, 2020. The purpose of the study is to provide evidential support for government policymaking so as to drive up more effective public policies by taking into consideration the variance in these social factors. It was found that the respondents’ party affiliation or preference, religious belief, and ethnicity, in addition to their health condition, gender, level of concern of contracting COVID-19, all affected their mask-wearing habits both in March, the initial coronavirus outbreak stage, and in August, when mask-wearing had been made mandatory by state governments. The study concludes that pandemic awareness campaigns must be run among all citizens, especially among African Americans, Muslims, and Republicans, who have the lowest rates of wearing masks, in order to protect themselves and others. It is recommended that complementary cognitive bias awareness programs should be implemented in non-Black and non-Muslim communities to eliminate social concerns that deter them from wearing masks.

Keywords: COVID-19 pandemic, ethnicity, mask-wearing, policymaking implications, political affiliations, religious beliefs, United States.

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