Search results for: human detection and identification

Authors: Yin Cheung Lam

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In 1949, the ratification of the Geneva Conventions heralded the international community’s adoption of a new universal and non-discriminatory approach to human rights in situations of conflict. However, with the proliferation of international terrorism after the 9/11 attacks on the United States (U.S.), the international community’s uneven and contradictory implementations of international humanitarian law (IHL) questioned its agenda of universal human rights. Specifically, the derogation from IHL has never been so pronounced in the U.S. led ‘War on Terror’. While an extensive literature has ‘assessed the impact’ of the implementation of the Geneva Conventions, limited attention has been paid to interrogating the ways in which the Geneva Conventions and its resulting implementation have functioned to discursively reproduce certain understandings of human rights between states and non-state actors. Through a discursive analysis of the Geneva Conventions and the conceptualization of human rights in relation to terrorism, this thesis problematises the way in which the U.S. has understood and reproduced understandings of human rights. Using the U.S. ‘War on Terror’ as an example, it seeks to extend previous analyses of the U.S.’ practice of IHL through a qualitative discursive analysis of the human rights content that appears in the Geneva Conventions in addition to the speeches and policy documents on the ‘War on Terror’.

Keywords: discursive analysis, human rights, non-state actors, war on terror

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

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Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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Authors: A. Kyprianou, A. Tjirkallis

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Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

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Authors: Mirco Tarozzi, Giacomo Pignagnoli, Andrea Benedetti

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The design of planning maintenance of civil structures often requires the evaluation of their level of safety in order to be able to choose which structure, and in which measure, it needs a structural retrofit. This work deals with the evaluation of the stiffness reduction of a scaled steel deck due to the presence of localized damages. The dynamic tests performed on it have shown the variability of its main frequencies linked to the gradual reduction of its rigidity. This deck consists in a steel grillage of four secondary beams and three main beams linked to a concrete slab. This steel deck is 6 m long and 3 m wide and it rests on two abutments made of concrete. By processing the signals of the accelerations due to a random excitation of the deck, the main natural frequencies of this bridge have been extracted. In order to assign more reliable parameters to the numerical model of the deck, some load tests have been performed and the mechanical property of the materials and the supports have been obtained. The two external beams have been cut at one third of their length and the structural strength has been restored by the design of a bolted plate. The gradual loss of the bolts and the plates removal have made the simulation of localized damage possible. In order to define the relationship between frequency variation and loss in stiffness, the identification of its natural frequencies has been performed, before and after the occurrence of the damage, corresponding to each step. The study of the relationship between stiffness losses and frequency shifts has been reported in this paper: the square of the frequency variation due to the presence of the damage is proportional to the ratio between the rigidities. This relationship can be used to quantify the loss in stiffness of a real scale bridge in an efficient way.

Keywords: damage detection, dynamic test, frequency shifts, operational modal analysis, steel bridge

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Authors: Wei Zheng, Mao Ji, Zhe Hou, Meng Huang, Bo Qi

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The transformer is the key equipment of the power system. Winding deformation is one of the main transformer defects, and timely and effective detection of the transformer winding deformation can ensure the safe and stable operation of the transformer to the maximum extent. When winding deformation occurs, the size, shape and spatial position of the winding will change, which directly leads to the change of magnetic flux leakage distribution. Therefore, it is promising to study the online detection method of the transformer winding deformation based on magnetic flux leakage characteristics, in which the key step is to study the optimal placement method of magnetic flux leakage sensors inside the transformer. In this paper, a simulation model of the transformer winding deformation is established to obtain the internal magnetic flux leakage distribution of the transformer under normal operation and different winding deformation conditions, and the law of change of magnetic flux leakage distribution due to winding deformation is analyzed. The results show that different winding deformation leads to different characteristics of the magnetic flux leakage distribution. On this basis, an optimized placement of magnetic flux leakage sensors inside the transformer is proposed to provide a basis for the online detection method of transformer winding deformation based on the magnetic flux leakage characteristics.

Keywords: magnetic flux leakage, sensor placement method, transformer, winding deformation

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

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Authors: Lottie Lane

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It is habitually assumed and stated that the World Bank should engage and comply with international human rights standards. However, the basis for holding the Bank to such standards is unclear. Most advocates of the idea invoke aspects of international law to argue that the Bank has existing obligations to act in compliance with human rights standards. The Bank itself, however, does not appear to accept such arguments, despite having endorsed the importance of human rights for a considerable length of time. A substantial challenge is that under the current international human rights law framework, the World Bank is considered a non-state actor, and as such, has no direct human rights obligations. In the absence of clear legal duties for the Bank, it is necessary to look at the tools available beyond the international human rights framework to encourage the Bank to comply with human rights standards. This article critically examines several bases for arguing that the Bank should comply and engage with human rights through its policies and practices. Drawing on the Bank’s own ‘good governance’ approach as well as the United Nations’ ‘human rights-based-approach’ to development, a new basis is suggested. First, the relationship between the World Bank and human rights is examined. Three perspectives are considered: (1) the legal position – what the status of the World Bank is under international human rights law, and whether it can be said to have existing legal human rights obligations; (2) the Bank’s own official position – how the Bank envisages its relationship with and role in the protection of human rights; and (3) the relationship between the Bank’s policies and practices and human rights (including how its attitudes are reflected in its policies and how the Bank’s operations impact human rights enjoyment in practice). Here, the article focuses on two examples – the (revised) 2016 Environmental and Social Safeguard Policies and the 2012 case-study regarding Gambella, Ethiopia. Both examples are widely considered missed opportunities for the Bank to actively engage with human rights. The analysis shows that however much pressure is placed on the Bank to improve its human rights footprint, it is extremely reluctant to do so explicitly, and the legal bases available are insufficient for requiring concrete, ex ante action by the Bank. Instead, the Bank’s own ‘good governance’ approach to development – which it has been advocating since the 1990s – can be relied upon. ‘Good governance’ has been used and applied by many actors in many contexts, receiving numerous different definitions. This article argues that human rights protection can now be considered a crucial component of good governance, at least in the context of development. In doing so, the article explains the relationship and interdependence between the two concepts, and provides three rationales for the Bank to take a ‘human rights-based approach’ to good governance. Ultimately, this article seeks to look beyond international human rights law and take a governance approach to provide a convincing basis upon which to argue that the World Bank should comply with human rights standards.

Keywords: World Bank, international human rights law, good governance, human rights-based approach

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Authors: L. Piñeiro, N. Cobas, L. Gómez-Limia, S. Martínez, I. Franco

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The swordfish (Xiphias gladius) is a large oceanic fish of high commercial value, which is widely distributed in waters of the world’s oceans. They are considered to be an important source of high quality proteins, vitamins and essential fatty acids, although only half of the population follows the recommendation of nutritionists to consume fish at least twice a week. Swordfish is consumed worldwide because of its low fat content and high protein content. It is generally sold as fresh, frozen, and as pieces or slices. The aim of this study was to evaluate the effect of salting and frying on the composition of the water-soluble vitamins (B₂, B₃, B₉ and B₁₂) and fat-soluble vitamins (A, D, and E) of swordfish. Three loins of swordfish from Pacific Ocean were analyzed. All the fishes had a weight between 50 and 70 kg and were transported to the laboratory frozen (-18 ºC). Before the processing, they were defrosted at 4 ºC. Each loin was sliced and salted in brine. After cleaning the slices, they were divided into portions (10×2 cm) and fried in olive oil. The identification and quantification of vitamins were carried out by high-performance liquid chromatography (HPLC), using methanol and 0.010% trifluoroacetic acid as mobile phases at a flow-rate of 0.7 mL min^-1. The UV-Vis detector was used for the detection of the water- and fat-soluble vitamins (A and D), as well as the fluorescence detector for the detection of the vitamin E. During salting, water and fat-soluble vitamin contents remained constant, observing an evident decrease in the values of vitamin B₂. The diffusion of salt into the interior of the pieces and the loss of constitution water that occur during this stage would be related to this significant decrease. In general, after frying water-soluble and fat-soluble vitamins showed a great thermolability with high percentages of retention with values among 50–100%. Vitamin B₃ is the one that exhibited higher percentages of retention with values close to 100%. However, vitamin B₉ presented the highest losses with a percentage of retention of less than 20%.

Keywords: frying, HPLC, salting, swordfish, vitamins

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Authors: Yustina Trihoni Nalesti Dewi

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Gross violations of human rights consisting of crime against humanity, genocide and war crime, are serious international crimes. Prohibition such crimes have obtain to the level of international norms of jus cogens based on conventions and customary international law. Therefore, the duty of the state to punish the crimes is obligatory. The legal consequence of jus cogens is obligation erga omnes which are a matter of state responsibility. When a state is not willing or neglects to do so in its national law, it results in state responsibility to be imposed by international human rights and humanitarian law. This article reviews the concept of jus cogens and obligatio erga omnes that appear as two sides of the same coin. It also explains how international human rights and humanitarian law set down the duty of the state to punish gross violations of human rights.

Keywords: duty of states, gross violations of human rights, jus cogens, obligatio erga omnes

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Abewardhana Arachchi Bandula Dimuthu Priyadarshana Abewardhana, Rasika Nirosh Gonapinuwala Vithanage, Karawe Thanthreege Amila Madusanka Perera, Asanka Sanjeewa Karunarathne, Navullage Mayuri Radhika Perera

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The phenomenon of irregular migration and human trafficking presents multifaceted challenges to Sri Lanka, with specific focus on the migration routes to the United Arab Emirates (UAE), the Sultanate of Oman, and Malaysia. This research critically assesses the efficacy of a pilot project instituted at Bandaranaike International Airport aimed at the identification and deterrence of potential irregular migrants. Additionally, the study conducts a nuanced analysis of the geographical tendencies pertaining to passengers who revise their migration intentions at the airport. Pertinently, the findings indicate that Colombo and Gampaha Districts emerge as the most susceptible to human trafficking, with Galle, Nuwaraeliya, Rathnapura, and Polonnaruwa Districts following as areas of elevated concern, particularly within the framework of the 'visit visa' scenario. These insights emanate from an extensive data collection period spanning 50 days of the pilot project, encompassing 1,479 passengers, of which 46 returnees reported to the Safe Migration Promotion Unit. The research is founded on the twin objectives of comprehending the motivations of passengers and evaluating the effectiveness of interventions, with a view to devising precision-targeted prevention strategies. Through this endeavor, the study actively contributes to the safeguarding of the rights and welfare of migrants, significantly advancing the ongoing battle against irregular migration.

Keywords: irregular migration, human trafficking, airport interventions, geographic trends

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Authors: Chih-Yi Ho, Tzu-Fang Chang, Chih-Chia Huang, Chia-Yen Lee

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In dental clinics, the dentists use the periapical radiography image to assess the effectiveness of endodontic treatment of teeth with chronic apical periodontitis. Periapical radiography images are taken at different times to assess alveolar bone variation before and after the root canal treatment, and furthermore to judge whether the treatment was successful. Current clinical assessment of apical tissue recovery relies only on dentist personal experience. It is difficult to have the same standard and objective interpretations due to the dentist or radiologist personal background and knowledge. If periapical radiography images at the different time could be registered well, the endodontic treatment could be evaluated. In the image registration area, it is necessary to assign representative control points to the transformation model for good performances of registration results. However, detection of representative control points (feature points) on periapical radiography images is generally very difficult. Regardless of which traditional detection methods are practiced, sufficient feature points may not be detected due to the low-contrast characteristics of the x-ray image. Barnard detector is an algorithm for feature point detection based on grayscale value gradients, which can obtain sufficient feature points in the case of gray-scale contrast is not obvious. However, the Barnard detector would detect too many feature points, and they would be too clustered. This study uses the local extrema of clustering feature points and the suppression radius to overcome the problem, and compared different feature point detection methods. In the preliminary result, the feature points could be detected as representative control points by the proposed method.

Keywords: feature detection, Barnard detector, registration, periapical radiography image, endodontic treatment

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Authors: Hossam M. Moftah, Aboul Ella Hassanien

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In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

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Authors: Yrfet Shkreli

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To determine the content of human rights norms in national constitutions, international law - in the form of treaties, declarations and case law from international monitoring bodies, and comparative case law from other countries - is often discussed in the judgments of domestic courts. This paper explores the extent to which international law has influenced domestic human rights case law in Africa. The paper first explores how the human rights provisions of African constitutions came into being before turning to the role played by international law in the constitutional order of various African states and how treaties, declarations and findings of international monitoring bodies have been used in African countries to interpret and expand on constitutional human rights provisions.

Keywords: European Union, global governance, globalization, normative power

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Authors: Nougrara Zineb

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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

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Authors: Khawla Askri, Mohamed Haythem Msaddek, AbdelAziz Sebei

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Climate change combined with the increase in anthropogenic activities will affect coastal groundwater systems around the world and, more particularly, the Cap Bon region in the North East of Tunisia. This study aims to study the impact of climate change and human stress on the salinization and quantification of groundwater in the Wadi Chiba watershed. In this regard, a hydro-climatological study and a hydrogeological study were carried out based on the characterization of the aquifer system of the eastern coast at the level of the watershed of Wadi Chiba in order to seek to identify, first of all, the degradation of the state of the aquifer on the quantitative level by the study of the piezometric and its evolution over time. Secondly, we sought to identify the degradation of the state of the aquifer qualitatively by using the geochemical method, in particular the major elements, to assess the mineralization of the aquifer water and understand its hydrogeochemical functioning. The study of the Na + / Cl- and Ca2 + / Mg2 + chemical relationships confirmed the presence of a marine intrusion downstream of the Wadi Chiba watershed northeast of Cap-Bon accompanied by a piezometric depression. For this purpose, we proceeded to: 1) Mapping of both piezometric data and salinity. 2) The interpretation of the mapping results. 3)Identification of the origin of the localized deterioration in the quality of the aquifer water. Finally, the analysis of the results showed that the scarcity of water is already forcing human actions in the Chiba watershed due to the irrigation of agricultural lands and the overexploitation of the water table in the study area.

Keywords: climate change, human activities, water table, Wadi Chiba watershed, piezometric depression, marine intrusion

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Lilia M. Fernando, Matthew K. Vasher, Evangelyn C. Alocilja

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This paper describes the development of a DNA-based nanobiosensor to detect the dengue virus in mosquito using electrically active magnetic (EAM) nanoparticles as the concentrator and electrochemical transducer. The biosensor detection encompasses two sets of oligonucleotide probes that are specific to the dengue virus: the detector probe labeled with the EAM nanoparticles and the biotinylated capture probe. The DNA targets are double hybridized to the detector and the capture probes and concentrated from nonspecific DNA fragments by applying a magnetic field. Subsequently, the DNA sandwiched targets (EAM-detector probe–DNA target–capture probe-biotin) are captured on streptavidin modified screen printed carbon electrodes through the biotinylated capture probes. Detection is achieved electrochemically by measuring the oxidation–reduction signal of the EAM nanoparticles. Results indicate that the biosensor is able to detect the redox signal of the EAM nanoparticles at dengue DNA concentrations as low as 10 ng/ul.

Keywords: dengue, magnetic nanoparticles, mosquito, nanobiosensor

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Authors: Tareq AlNuaim, Mubashir Alam, Abdulrazaq Aldowesh

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The usage of micro-Unmanned Ariel Vehicles (UAVs) has witnessed an enormous increase recently. Detection of such drones became a necessity nowadays to prevent any harmful activities. Typically, such targets have low velocity and low Radar Cross Section (RCS), making them indistinguishable from clutter and phase noise. Multiple-Input Multiple-Output (MIMO) Radars have many potentials; it increases the degrees of freedom on both transmit and receive ends. Such architecture allows for flexibility in operation, through utilizing the direct access to every element in the transmit/ receive array. MIMO systems allow for several array processing techniques, permitting the system to stare at targets for longer times, which improves the Doppler resolution. In this paper, a 2×2 MIMO radar prototype is developed using Software Defined Radio (SDR) technology, and its performance is evaluated against a slow-moving low radar cross section micro-UAV used by hobbyists. Radar cross section simulations were carried out using FEKO simulator, achieving an average of -14.42 dBsm at S-band. The developed prototype was experimentally evaluated achieving more than 300 meters of detection range for a DJI Mavic pro-drone

Keywords: digital beamforming, drone detection, micro-UAV, MIMO, phased array

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Authors: Yu. I. Pigolkin, M. A. Garcia Corro

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Age determination of unknown dead bodies in forensic personal identification is a complicated process which involves the application of numerous methods and techniques. Skeletal remains are less exposed to influences of environmental factors. In order to enhance the accuracy of forensic age estimation additional properties of bones correlating with age are required to be revealed. Material and Methods: Dimensional examination of the sella turcica was carried out on cadavers with the cranium opened by a circular vibrating saw. The sample consisted of a total of 90 Russian subjects, ranging in age from two months and 87 years. Results: The tendency of dimensional variations throughout life was detected. There were no observed gender differences in the morphometry of the sella turcica. The shared use of the sella turcica depth and length values revealed the possibility to categorize an examined sample in a certain age period. Conclusions: Based on the results of existing methods of age determination, the morphometry of the sella turcica can be an additional characteristic, amplifying the received values, and accordingly, increasing the accuracy of forensic biological age diagnosis.

Keywords: age–related changes in bone structures, forensic personal identification, sella turcica morphometry, body identification

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Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Mona Baniahmadi, Saied Haghanifar

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Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand for planning, managing inventory, and distribution. This study precisely aims at learning to know the RFID technology and at explaining how it can concretely be used for supply chain management and how it can help improving it in the case of Hejrat Company which is located in Iran and works on the distribution of medical drugs and cosmetics. This study uses some statistical analysis to calculate the expected benefits of an integrated RFID system on supply chain obtained through competitive advantages increases with decreasing cost factor. The study investigates how the cost of storage process, labor cost, the cost of missing goods, inventory management optimization, on-time delivery, order cost, lost sales and supply process optimization affect the performance of the integrated RFID supply chain regarding cost factors and provides a competitive advantage.

Keywords: cost, competitive advantage, radio frequency identification, supply chain

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Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

Abstract:

Catecholamines are vital neurotransmitters that mediate a variety of central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, optical techniques for the detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid-modified enzymatic sensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence as well as electrochemical sensing strategy for catecholamines detection.

Keywords: biosensors, catecholamines, fluorescence, enzymes

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Authors: J. G. Batista, K. N. Sousa, ¬J. L. Nunes, R. L. S. Sousa, G. A. P. Thé

Abstract:

This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Fabrizio Iezzi, Claudio Valente

Abstract:

The viscous damping in dynamic systems can be proportional or non-proportional. In the first case, the mode shapes are real whereas in the second case they are complex. From an engineering point of view, the complexity of the mode shapes is important in order to quantify the non-proportional damping. Different indices exist to provide estimates of the modal complexity. These indices are or not zero, depending whether the mode shapes are not or are complex. The modal density problem arises in the experimental identification when the dynamic systems have close modal frequencies. Depending on the entity of this closeness, the mode shapes can hold fictitious imaginary quantities that affect the values of the modal complexity indices. The results are the failing in the identification of the real or complex mode shapes and then of the proportional or non-proportional damping. The paper aims to show the influence of the modal density on the values of these indices in case of both proportional and non-proportional damping. Theoretical and pseudo-experimental solutions are compared to analyze the problem according to an appropriate mechanical system.

Keywords: complex mode shapes, dynamic systems identification, modal density, non-proportional damping

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Authors: Po-Hui Yang, Jing-Min Chen, Po-Yu Kuo, Chia-Chun Wu

Abstract:

This paper proposed a high resolution Vernier Delay Line (VDL) measurement circuit with coarse and fine detection mechanism, which improved the trade-off problem between high resolution and less delay cells in traditional VDL circuits. And the measuring time of proposed measurement circuit is also under the high resolution requests. At first, the testing range of input signal which proposed high resolution delay line is detected by coarse detection VDL. Moreover, the delayed input signal is transmitted to fine detection VDL for measuring value with better accuracy. This paper is implemented at 0.18μm process, operating frequency is 100 MHz, and the resolution achieved 2.0 ps with only 16-stage delay cells. The test range is 170ps wide, and 17% stages saved compare with traditional single delay line circuit.

Keywords: vernier delay line, D-type flip-flop, DFF, metastable phenomenon

Procedia PDF Downloads 594

Authors: J. U. Santhosh Kumar, V. Krishna, Sebin Sebastian, G. S. Seethapathy, G. Ravikanth, R. Uma Shaanker

Abstract:

Food is one of the basic needs of human beings. It requires the normal function of the body part and a healthy growth. Recently, food adulteration increases day by day to increase the quantity and make more benefit. Animal source foods can provide a variety of micronutrients that are difficult to obtain in adequate quantities from plant source foods alone. Particularly in the meat industry, products from animals are susceptible targets for fraudulent labeling due to the economic profit that results from selling cheaper meat as meat from more profitable and desirable species. This work presents an overview of the main PCR-based techniques applied to date to verify the authenticity of beef meat and meat products from beef species. We were analyzed 25 market beef samples in South India. We examined PCR methods based on the sequence of the cytochrome b gene for source species identification. We found all sample were sold as beef meat as Bos Taurus. However, interestingly Male meats are more valuable high price compare to female meat, due to this reason most of the markets samples are susceptible. We were used sex determination gene of cattle like TSPY(Y-encoded, testis-specific protein TSPY is a Y-specific gene). TSPY homologs exist in several mammalian species, including humans, horses, and cattle. This gene is Y coded testis protein genes, which only amplify the male. We used multiple PCR products form species-specific “fingerprints” on gel electrophoresis, which may be useful for meat authentication. Amplicons were obtained only by the Cattle -specific PCR. We found 13 market meat samples sold as female beef samples. These results suggest that the species-specific PCR methods established in this study would be useful for simple and easy detection of adulteration of meat products.

Keywords: authentication, meat products, species-specific, TSPY

Procedia PDF Downloads 371

Authors: Luna Shamieh

Abstract:

Various players are part of the game in an asymmetric war, all making efforts to provide human security to their own adherents. Although a fragile state is not able to provide sufficient and comprehensive services, it still provides special services and security to the elite; the insurgents as well provide services and security to their associates. The humanitarian organisations, on the other hand, provide some fundamental elements of human security, but only in the regions, they are able to access when possible (if possible). The counterinsurgents (security forces of the state and intervention forces) operate within a narrow band defined by the vision of the responsibility to protect and the perspective of the resolution of the conflict through combat; hence, the possibility to provide human security is shaken at this end. This article examines how each player provides human security from the perspective of freedom from want in order to secure basic and strategic needs, freedom from fear through providing protection against all kinds of violence, and the freedom to live in dignity. It identifies a vicious cycle caused by the intervention of the different players causing a centrifugal force that may lead to disintegration of the nation under war.

Keywords: asymmetric war, counterinsurgency, fragile state, human security, insurgency

Procedia PDF Downloads 329