Search results for: normalized subband adaptive filter (NSAF)

Authors: Ankur Gupta, Jayant Raj Saurav, Shantanu Bhattacharya

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In this work we report an effective water filtration system based on the photo catalytic performance of semiconducting dense nano-brushes under natural sunlight. During thin-film photocatalysis usually performed by a deposited layer of photocatalyst, a stagnant boundary layer is created near the catalyst which adversely affects the rate of adsorption because of diffusional restrictions. One strategy that may be used is to disrupt this laminar boundary layer by creating a super dense nanostructure near the surface of the catalyst. Further it is adequate to fabricate a structured filter element for a through pass of the water with as grown nanostructures coming out of the surface of such an element. So, the dye remediation is performed through solar means. This remediation was initially limited to lower efficiency because of diffusional restrictions but has now turned around as a fast process owing to the development of the filter materials with standing out dense nanostructures. The effect of increased surface area due to microholes on fraction adsorbed is also investigated and found that there is an optimum value of hole diameter for maximum adsorption.

Keywords: nano materials, photocatalysis, waste water treatment, water remediation

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Authors: Justin A. Udie, Subhes C. Bhatthacharyya, Leticia Ozawa-Meida

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The impact of climate change is severe in the Niger Delta and critical oil and gas infrastructures are vulnerable. This is partly due to lack of specific impact assessment framework to assess impact indices on both existing and new infrastructures. The purpose of this paper is to develop a framework for the assessment of climate change impact on critical oil and gas infrastructure in the region. Comparative and documentary methods as well as analysis of frameworks were used to develop a flexible, integrated and conceptual four dimensional framework underpinning; 1. Scoping – the theoretical identification of inherent climate burdens, review of exposure, adaptive capacities and delineation of critical infrastructure; 2. Vulnerability assessment – presents a systematic procedure for the assessment of infrastructure vulnerability. It provides real time re-scoping, practical need for data collection, analysis and review. Physical examination of systems is encouraged to complement the scoped data and ascertain the level of exposure to relevant climate risks in the area; 3. New infrastructure – consider infrastructures that are still at developmental level. It seeks to suggest the inclusion of flexible adaptive capacities in original design of infrastructures in line with climate threats and projections; 4. The Mainstreaming Climate Impact Assessment into government’s environmental decision making approach. Though this framework is designed specifically for the estimation of exposure, adaptive capacities and criticality of vulnerable oil and gas infrastructures in the Niger Delta to climate burdens; it is recommended for researchers and experts as a first-hand generic and practicable tool which can be used for the assessment of other infrastructures perceived as critical and vulnerable. The paper does not provide further tools that synch into the methodological approach but presents pointers upon which a pragmatic methodology can be developed.

Keywords: adaptation, assessment, conceptual, climate, change, framework, vulnerability

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Authors: Josselyn Mata Calidonio, Arianna I. Maddox, Kimberly Hamad-Schifferli

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Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.

Keywords: adaptive immunoassay, detecting unknown viruses, gold nanoparticles, paper immunoassay, repurposing antibodies

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Authors: A. Harras, A. Tsuji, K. Terada

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Tracking of moving people has gained a matter of great importance due to rapid technological advancements in the field of computer vision. The objective of this study is to design a motion based detection and tracking multiple walking pedestrians randomly in different directions. In our proposed method, Gaussian mixture model (GMM) is used to determine moving persons in image sequences. It reacts to changes that take place in the scene like different illumination; moving objects start and stop often, etc. Background noise in the scene is eliminated through applying morphological operations and the motions of tracked people which is determined by using the Kalman filter. The Kalman filter is applied to predict the tracked location in each frame and to determine the likelihood of each detection. We used a benchmark data set for the evaluation based on a side wall stationary camera. The actual scenes from the data set are taken on a street including up to eight people in front of the camera in different two scenes, the duration is 53 and 35 seconds, respectively. In the case of walking pedestrians in close proximity, the proposed method has achieved the detection ratio of 87%, and the tracking ratio is 77 % successfully. When they are deferred from each other, the detection ratio is increased to 90% and the tracking ratio is also increased to 79%.

Keywords: automatic detection, tracking, pedestrians, counting

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Authors: Piotr Kacejko, Mariusz Duk, Miroslaw Wendeker

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This paper presents an adaptive controller to track the maximum power point of a photovoltaic modules (PV) under fast irradiation change on the city-bus roof. Photovoltaic systems have been a prominent option as an additional energy source for vehicles. The Municipal Transport Company (MPK) in Lublin has installed photovoltaic panels on its buses roofs. The solar panels turn solar energy into electric energy and are used to load the buses electric equipment. This decreases the buses alternators load, leading to lower fuel consumption and bringing both economic and ecological profits. A DC–DC boost converter is selected as the power conditioning unit to coordinate the operating point of the system. In addition to the conversion efficiency of a photovoltaic panel, the maximum power point tracking (MPPT) method also plays a main role to harvest most energy out of the sun. The MPPT unit on a moving vehicle must keep tracking accuracy high in order to compensate rapid change of irradiation change due to dynamic motion of the vehicle. Maximum power point track controllers should be used to increase efficiency and power output of solar panels under changing environmental factors. There are several different control algorithms in the literature developed for maximum power point tracking. However, energy performances of MPPT algorithms are not clarified for vehicle applications that cause rapid changes of environmental factors. In this study, an adaptive MPPT algorithm is examined at real ambient conditions. PV modules are mounted on a moving city bus designed to test the solar systems on a moving vehicle. Some problems of a PV system associated with a moving vehicle are addressed. The proposed algorithm uses a scanning technique to determine the maximum power delivering capacity of the panel at a given operating condition and controls the PV panel. The aim of control algorithm was matching the impedance of the PV modules by controlling the duty cycle of the internal switch, regardless of changes of the parameters of the object of control and its outer environment. Presented algorithm was capable of reaching the aim of control. The structure of an adaptive controller was simplified on purpose. Since such a simple controller, armed only with an ability to learn, a more complex structure of an algorithm can only improve the result. The presented adaptive control system of the PV system is a general solution and can be used for other types of PV systems of both high and low power. Experimental results obtained from comparison of algorithms by a motion loop are presented and discussed. Experimental results are presented for fast change in irradiation and partial shading conditions. The results obtained clearly show that the proposed method is simple to implement with minimum tracking time and high tracking efficiency proving superior to the proposed method. This work has been financed by the Polish National Centre for Research and Development, PBS, under Grant Agreement No. PBS 2/A6/16/2013.

Keywords: adaptive control, photovoltaic energy, city bus electric load, DC-DC converter

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Authors: Rana Sameeh

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The city is the greatest symbol of human civilization and has been built for safety and comfort. However, uncontrolled urban growth caused some anonymous and unsightly images of the cities such as unused or abandoned spaces. When social interaction is missed in a public space it means the public space is lost since public spaces reflect the social life and interaction of people. Accordingly; this space became one of the most meaningless parts of the cities and has broken the continuity of the urban fabric. Lost urban spaces are the leftover unstructured landscape within the urban fabric. They are generally the unrecognized urban areas that are in need of redesign, since they have a great value that can add to their surrounding urban context. The research significance lies within the importance of urban open spaces, their value and their impact on the urban fabric. The research also addresses the reuse and reclamation of lost urban spaces in order to increase the percentage of green areas along the urban fabric, provide urban open spaces, develop a sustainable approach towards urban landscape and enhance the quality of the public open space and user experience. In addition, the reuse of lost space will give it the identity and function it lacks while also providing places for presence, spending time and observing. Creating continuity in a broken urban fabric represents an exploratory process in the relationship between infrastructure and the urban fabric and seeks to establish an architectural solution to leftover space within the city. In doing so, the research establishes a framework (criteria) for adaptive reuse of lost urban space throughout inductive and deductive methodology, analytical methodology; by analyzing some relevant examples and similar cases of lost spaces and finally through field methodology; by applying the achieved criteria on a case study in Alexandria and carrying on SWOT analysis and evaluation of the potentials of this case study.

Keywords: adaptive reuse, lost urban space, quality of public open space, urban fabric

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Authors: Sumayya S.

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Making cities adaptive and inclusive is one among the inherent goal and challenge for contemporary cities. This is a serious concern when the urban transformations occur in varying magnitude due to visible and invisible factors. One type of visibly invisible factor is ecommerce and its expanding operation that is understood to cause changes to the conventional spatial structure positively and negatively. With the continued growth in e-commerce activities and its future potential, market analysts, media, and even retailers have questioned the importance of a future presence of traditional Brick-and-mortar stores in cities as a critical element, with some even referring to the repeated announcement of the closure of some store chains as the end of the online shopping era. Essentially this raises the question of how adaptive and inclusive the cities are to the dynamics of transformative changes that are often unseen. People have become more comfortable with seating inside and door delivery systems, and this increased change in usage of public spaces, especially the commercial corridors. Through this research helped in presetting a new approach for planning and designing commercial activities centers and also presents the impact of ecommerce on the urban fabric, such as division and fragmentation of space, showroom syndrome, reconceptualization of space, etc., in a critical way. The changes are understood by analyzing the e-commerce logistic process. Based on the inferences reach at the conclusion for the need of an integrated approach in the field of planning and designing of public spaces for the sustainable omnichannel retailing. This study was carried out with the following objectives Monitoring the impact of e commerce on the traditional shopping space. Explore the new challenges and opportunities faced by the urban form. Explore how adaptive and inclusive our cities are to the dynamics of transformative changes caused by ecommerce.

Keywords: E-commerce, shopping streets, online environment, offline environment, shopping factors

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.

Keywords: cloud computing, virtualization, virtual desktop, VDaaS

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

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Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

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Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Z. Mortezaie, H. Hassanpour, S. Asadi Amiri

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Captured images may suffer from Gaussian blur due to poor lens focus or camera motion. Unsharp masking is a simple and effective technique to boost the image contrast and to improve digital images suffering from Gaussian blur. The technique is based on sharpening object edges by appending the scaled high-frequency components of the image to the original. The quality of the enhanced image is highly dependent on the characteristics of both the high-frequency components and the scaling/gain factor. Since the quality of an image may not be the same throughout, we propose an adaptive unsharp masking method in this paper. In this method, the gain factor is computed, considering the gradient variations, for individual pixels of the image. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed unsharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.

Keywords: unsharp masking, blur image, sub-region gradient, image enhancement

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Authors: Alireza Pouladkhan, Mohammad Yavari Foroushani, Ali Mortazavi

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This paper presents a finite element model for a sandwich plate containing a piezoelectric core. A sandwich plate with a piezoelectric core is constructed using the shear mode of piezoelectric materials. The orientation of poling vector has a significant effect on deflection and stress induced in the piezo-actuated adaptive sandwich plate. In the present study, the influence of this factor for a clamped-clamped-free-free and simple-simple-free-free square sandwich plate is investigated using Finite Element Method. The study uses ABAQUS (v.6.7) software to derive the finite element model of the sandwich plate. By using this model, the study gives the influences of the poling vector angle on the response of the smart structure and determines the maximum transverse displacement and maximum stress induced.

Keywords: finite element method, sandwich plate, poling vector, piezoelectric materials, smart structure, electric enthalpy

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Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: B. S.Akhmetov, S. T. Akhmetova, D. N. Nadeyev, V. Yu. Yegorov, V. V. Smogoonov

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Estimated probabilities of errors of the first and second kind for nonideal biometrics-neural transducers 256 outputs, the construction of nomograms based error probability of 'own' and 'alien' from the mathematical expectation and standard deviation of the normalized measures Hamming.

Keywords: modeling, errors, probability, biometrics, neural network, authentication

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Authors: Sara Tokhi Arab, Tariq Salari, Ryozo Noguchi, Tofael Ahamed

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Land suitability analysis is essential for table grape cultivation in order to increase its production and productivity under the dry condition of Afghanistan. In this context, the main aim of this paper was to determine the suitable locations for vineyards based on satellite remote sensing and GIS (geographical information system) in Kabul Province of Afghanistan. The Landsat8 OLI (operational land imager) and thermal infrared sensor (TIRS) and shuttle radar topography mission digital elevation model (SRTM DEM) images were processed to obtain the normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), land surface temperature (LST), and topographic criteria (elevation, aspect, and slope). Moreover, Jaxa rainfall (mm per hour), soil properties information are also used for the physical suitability of vineyards. Besides, socio-economic criteria were collected through field surveys from Kabul Province in order to develop the socio-economic suitability map. Finally, the suitable classes were determined using weighted overly based on a reclassification of each criterion based on AHP (Analytical Hierarchy Process) weights. The results indicated that only 11.1% of areas were highly suitable, 24.8% were moderately suitable, 35.7% were marginally suitable and 28.4% were not physically suitable for grapes production. However, 15.7% were highly suitable, 17.6% were moderately suitable, 28.4% were marginally suitable and 38.3% were not socio-economically suitable for table grapes production in Kabul Province. This research could help decision-makers, growers, and other stakeholders with conducting precise land assessments by identifying the main limiting factors for the production of table grapes management and able to increase land productivity more precisely.

Keywords: vineyards, land physical suitability, socio-economic suitability, AHP

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Z. Abdollahi Biron, P. Pisu

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Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: fault diagnostics, communication network, connected vehicles, packet drop out, platoon

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Zerihun Yohannes Amare Id, Bernhard Freyer, Ky Serge Stephane, Ouéda Adama, Blessing Mudombi, Jean Nzuma, Mekonen Getachew Abebe, Adane Tesfaye, Birtukan Atinkut Asmare, Tesfahun Asmamaw Kassie

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The study was conducted in Ethiopia (Zege Catchment) (ZC), Zimbabwe (Upper Save Catchment) (USC), and Burkina Faso (Nakambe Catchment) (NC). The study utilized a quantitative approach with 180 participants and complemented it with qualitative methods, including 33 key informant interviews and 6 focus group discussions. Households in ZC (58%), NC (55%), and US (40%) do not cover their household food consumption from crop production. The households rely heavily on perennial cash crops rather than annual crop production. Exposure indicators in ZC (0.758), USC (0.774), and NC (0.944), and sensitivity indicators in ZC (0.849) and NC (0.937) show statistically significant and high correlation with vulnerability. In the USC, adaptive capacity (0.746) and exposure (0.774) are also statistically significant and highly correlated with vulnerability. Vulnerability levels of the NC are very high (0.75) (0.85 female and 0.65 male participants) compared to the USC (0.66) (0.69 female and 0.61 male participants) and ZC (0.47) (0.34 female and 0.58 male participants). Female-headed households had statistically significantly lower vulnerability index compared to males in ZC, while male-headed households had statistically significantly lower vulnerability index compared to females in USC and NC. The reason is land certification in ZC (80%) is higher than in the US (10%) and NC (8%). Agroforestry practices variables across the study catchments had statistically significant contributions to households' adaptive capacity. We conclude that agroforestry practices do have substantial benefits in increasing women's adaptive capacity and reducing their vulnerability to climate change and food insecurity.

Keywords: climate change vulnerability, agroforestry, gender, food security, Sub-Saharan Africa

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, A. Abu-Siada

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Dissolved Gas Analysis is one of impressive technique to detect and predict internal fault of transformers by using gas generated by transformer oil sample. A number of methods are used to interpret the dissolved gas from transformer oil sample: Doernenberg Ratio Method, IEC (International Electrotechnical Commission) Ratio Method, and Duval Triangle Method. While the assessment of dissolved gas within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straight forward as it depends on personnel expertise more than mathematical formulas. To get over this limitation, this paper is aimed at improving the interpretation of Doernenberg Ratio Method, IEC Ratio Method, and Duval Triangle Method using Two Stages Adaptive Neuro-Fuzzy Inference System (ANFIS). Dissolved gas analysis data from 520 faulty transformers was analyzed to establish the proposed ANFIS model. Results show that the developed ANFIS model is accurate and can standardize the dissolved gas interpretation process with accuracy higher than 90%.

Keywords: ANFIS, dissolved gas analysis, Doernenberg ratio method, Duval triangular method, IEC ratio method, transformer

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: E. Bittar, A. Quiñonez, F. Mencia, E. Aguero, M. Delgado, V. Arriola, R. López

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In the western region of Paraguay, the poor condition of the roads has negatively affected the development of this zone, where the absence of petrous material has led engineers to opt for the stabilization of soils with lime or cement as the main structure for bases and subbases of these roads. In several areas of this region, high sulfate contents have been found both in groundwater and in soils, which, when reacted with lime or cement, generate a new problem instead of solving it. On the other hand, the use of industrial waste as granulated slag and fly ash proved to be a sustainable practice widely used in the manufacture of cement, and now also, in the stabilization of soils worldwide. Works related to soils containing sulfates stabilized either with granulated slag or fly ash and lime shown a good performance in their mechanical behaviour. This research seeks to evaluate the mechanical behaviour of soils with high contents of sulfates stabilized with lime by curing them both, at the normalized temperature (23 ± 2 °C) and at 40 ± 2 °C. Moreover, it attempts to asses if the addition of rice husk ash has a positive influence on the new geomaterial. The 40 ± 2 °C curing temperature was selected trying to simulate the average local temperature in summer and part of spring session whereas rice husk ash is an affordable waste produced in the region. An extensive experimental work, which includes unconfined compression, durability and free swell tests were carried out considering different dry unit weights, lime content and the addition of 20% of rice husk ash. The results showed that the addition of rice husk ash increases the resistance and durability of the material and decreases the expansion of this, moreover, the specimens cured at a temperature of 40 ± 2 °C showed higher resistance, better durability and lower expansion compared to those cured at the normalized temperature of 23 ± 2 °C.

Keywords: durability, expansion, lime stabilization, rice husk ash, sulfate

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Authors: Sergei Voychuk

Abstract:

Introduction: Adaptive response (AR) is a manifestation of radiation hormesis, which deal with the radiation resistance that may be increased with the pretreatment with small doses of radiation. In the current study, we evaluated the potency of radiofrequency EMF to induce the AR mechanisms and to increase a resistance to UV light. Methods: Saccharomyces cerevisiae yeast strains, which were created to study induction of mutagenesis and recombination, were used in the study. The strains have mutations in rad2 and rad54 genes, responsible for DNA repair: nucleotide excision repair (PG-61), postreplication repair (PG-80) and mitotic (crossover) recombination (T2). An induction of mutation and recombination are revealed due to the formation of red colonies on agar plates. The PG-61 and T2 are UV sensitive strains, while PG-80 is sensitive to ionizing radiation. Extremely high frequency electromagnetic field (EHF-EMF) was used. The irradiation was performed in floating mode and frequency changed during exposure from 57 GHz to 62 GHz. The power of irradiation was 100 mkW, and duration of exposure was 10 and 30 min. Treatment was performed at RT and then cells were stored at 28° C during 1 h without any exposure but after that they were treated with UV light (254nm) for 20 sec (strain T2) and 120 sec (strain PG-61 and PG-80). Cell viability and quantity of red colonies were determined after 5 days of cultivation on agar plates. Results: It was determined that EHF-EMF caused 10-20% decrease of viability of T2 and PG-61 strains, while UV showed twice stronger effect (30-70%). EHF-EMF pretreatment increased T2 resistance to UV, and decreased it in PG-61. The PG-80 strain was insensitive to EHF-EMF and no AR effect was determined for this strain. It was not marked any induction of red colonies formation in T2 and PG-80 strain after EHF or UV exposure. The quantity of red colonies was 2 times more in PG-61 strain after EHF-EMF treatment and at least 300 times more after UV exposure. The pretreatment of PG-61 with EHF-EMF caused at least twice increase of viability and consequent decrease of amount of red colonies. Conclusion: EHF-EMF may induce AR in yeast cells and increase their viability under UV treatment.

Keywords: Saccharomyces cerevisiae, EHF-EMF, UV light, adaptive response

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

Abstract:

An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

Procedia PDF Downloads 101

Authors: Wang Yongdong, Yeneayehu Fenetahun, You Yuan, Ogbue Chukwuka, Yahaya Ibrahim, Xu Xinwen

Abstract:

This paper explores an innovative Ethiopian approach to combatting desertification, focusing on the semi-arid savanna grasslands in Southern Ethiopia. The study investigates the multifaceted strategies employed by Ethiopian communities, governmental bodies, and non-governmental organizations to address desertification challenges in the region. Through an analysis of legislative frameworks, community engagement, afforestation programs, and sustainable land management techniques, this research highlights the efficacy of Ethiopia's strategy in reducing the effects of desertification. The results emphasize how crucial it is to build effective measures for halting desertification in fragile ecosystems by utilizing local knowledge, community involvement, and adaptive governance. In addition, this study also addresses how the Ethiopian approach may be applied to other areas with comparable environmental problems. In summary, this research adds significant perspectives to the worldwide conversation about desertification and provides useful guidance for sustainable land use.

Keywords: adaptive governance, community engagement, desertification, policy frameworks

Procedia PDF Downloads 27

Authors: Anurag Mishra, Prabhat Kumar Singh, Anurag Ohri, Shishir Gaur

Abstract:

Streams and rivulets are crucial in maintaining river networks and their hydrology, influencing downstream ecosystems, and connecting different watersheds of urban and rural areas. The river Assi, an urban river, once a lifeline for the locals, has degraded over time. Evidence, such as the presence of paleochannels and patterns of water bodies and settlements, suggests that the river Assi was initially an alluvial stream or rivulet that originated near Rishi Durvasha Ashram near Prayagraj, flowing approximately 120 km before joining the river Ganga at Assi ghat in Varanasi. Presently, a major challenge is that nearly 90% of its original channel has been silted and disappeared, with only the last 8 km retaining some semblance of a river. It is possible that initially, the river Assi branched off from the river Ganga and functioned as a Yazoo stream. In this study, paleochannels of the river Assi were identified using Landsat 5 imageries and SRTM DEM. The study employed the Normalized Difference Vegetation Seasonality Index (NDVSI) and Principal Component Analysis (PCA) of the Normalized Difference Vegetation Index (NDVI) to detect these paleochannels. The average elevation of the sub-basin at the Durvasha Rishi Ashram of river Assi is 96 meters, while it reduces to 80 meters near its confluence with the Ganga in Varanasi, resulting in a 16-meter elevation drop along its course. There are 81 subbasins covering an area of 83,241 square kilometers. It is possible that due to the increased resistance in the flow of river Assi near urban areas of Varanasi, a new channel, Morwa, has originated at an elevation of 87 meters, meeting river Varuna at an elevation of 79 meters. The difference in elevation is 8 meters. Furthermore, the study explored the possibility of restoring the paleochannel of the river Assi and nearby ponds and water bodies to improve the river's base flow and overall hydrological conditions.

Keywords: River Assi, small river restoration, paleochannel identification, remote sensing, GIS

Procedia PDF Downloads 54

Authors: T. Abbas, J. McEvoy, E. Khan

Abstract:

Pesticide contamination in water supply is a common environmental problem in rural agricultural communities. Advanced water treatment processes such as membrane filtration and adsorption on activated carbon only remove pesticides from water without degrading them into less toxic/easily degradable compounds leaving behind contaminated brine and activated carbon that need to be managed. Rural communities which normally cannot afford expensive water treatment technologies need an economical and sustainable filter which not only treats pesticides from water but also degrades them into benign products. In this study, iron turning waste experimented as potential point-of-use filtration media for the removal/degradation of a mixture of six chlorinated pesticides (lindane, heptachlor, endosulfan, dieldrin, endrin, and DDT) in water. As a common and traditional medium for water filtration, sand was also tested along with iron turning waste. Iron turning waste was characterized using scanning electron microscopy and energy dispersive X-Ray analyzer. Four glass columns with different filter media layer configurations were set up: (1) only sand, (2) only iron turning, (3) sand and iron turning (two separate layers), and (4) sand, iron turning and sand (three separate layers). The initial pesticide concentration and flow rate were 2 μg/L and 10 mL/min. Results indicate that sand filtration was effective only for the removal of DDT (100%) and endosulfan (94-96%). Iron turning filtration column effectively removed endosulfan, endrin, and dieldrin (85-95%) whereas the lindane and DDT removal were 79-85% and 39-56%, respectively. The removal efficiencies for heptachlor, endosulfan, endrin, dieldrin, and DDT were 90-100% when sand and iron turning waste (two separate layers) were used. However, better removal efficiencies (93-100%) for five out of six pesticides were achieved, when sand, iron turning and sand (three separate layers) were used as filtration media. Moreover, the effects of water pH, amounts of media, and minerals present in water such as magnesium, sodium, calcium, and nitrate on the removal of pesticides were examined. Results demonstrate that iron turning waste efficiently removed all the pesticides under studied parameters. Also, it completely de-chlorinated all the pesticides studied and based on the detection of by-products, the degradation mechanisms for all six pesticides were proposed.

Keywords: pesticide contamination, rural communities, iron turning waste, filtration

Procedia PDF Downloads 247

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

Procedia PDF Downloads 368