Search results for: identification of unknown dead bodies

Authors: Michael Anton Kraus, Miriam Schuster, Geralt Siebert, Jens Schneider

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Polymers increasingly gained interest in construction materials over the last years in civil engineering applications. As polymeric materials typically show time- and temperature dependent material behavior, which is accounted for in the context of the theory of linear viscoelasticity. Within the context of this paper, the authors show, that some polymeric interlayers for laminated glass can not be considered as thermorheologically simple as they do not follow a simple TTSP, thus a methodology of identifying the thermorheologically complex constitutive bahavioir is needed. ‘Dynamical-Mechanical-Thermal-Analysis’ (DMTA) in tensile and shear mode as well as ‘Differential Scanning Caliometry’ (DSC) tests are carried out on the interlayer material ‘Ethylene-vinyl acetate’ (EVA). A navoel Bayesian framework for the Master Curving Process as well as the detection and parameter identification of the TTSPs along with their associated Prony-series is derived and applied to the EVA material data. To our best knowledge, this is the first time, an uncertainty quantification of the Prony-series in a Bayesian context is shown. Within this paper, we could successfully apply the derived Bayesian methodology to the EVA material data to gather meaningful Master Curves and TTSPs. Uncertainties occurring in this process can be well quantified. We found, that EVA needs two TTSPs with two associated Generalized Maxwell Models. As the methodology is kept general, the derived framework could be also applied to other thermorheologically complex polymers for parameter identification purposes.

Keywords: bayesian parameter identification, generalized Maxwell model, linear viscoelasticity, thermorheological complex

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Authors: G. V. Sai Soumya, Kalpesh Solanki, Sumit K. Choudhary

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Necropsy is another term used for an autopsy, which is known as death examination in the case of animals. It is a complete standardized procedure involving dissection, observation, interpretation, and documentation. Government Bodies like National Tiger Conservation Authority (NTCA) have given standard operating procedures for commencing the necropsies. Necropsies are rarely performed as compared to autopsies performed on human bodies. There are no databases which maintain the count of autopsies in wildlife, but the research in this area has shown a very small number of necropsies. Long back, wildlife forensics came into existence but is coming into light nowadays as there is an increase in wildlife crime cases, including the smuggling of trophies, pooching, and many more. Physical examination in cases of animals is not sufficient to yield fruitful information, and thus postmortem examination plays an important role. Postmortem examination helps in the determination of time since death, cause of death, manner of death, factors affecting the case under investigation, and thus decreases the amount of time required in solving cases. Increasing the rate of necropsies will help forensic veterinary pathologists to build standardized provision and confidence within them, which will ultimately yield a higher success rate in solving wildlife crime cases.

Keywords: necropsy, wildlife crime, postmortem examination, forensic application

Procedia PDF Downloads 134

Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Aysun Sezer

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Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

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Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner

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Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.

Keywords: USB, device, cyber security, attack, detection

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Authors: Doyoung Kim, Hyo Seon Park

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Studies of System Identification(SI) based on Structural Health Monitoring(SHM) have actively conducted for structural safety. Recently SI techniques have been rapidly developed with output-only SI paradigm for estimating modal parameters. The features of these output-only SI methods consist of Frequency Domain Decomposition(FDD) and Stochastic Subspace Identification(SSI) are using the algorithms based on orthogonal decomposition such as singular value decomposition(SVD). But the SVD leads to high level of computational complexity to estimate modal parameters. This paper proposes the technique to estimate mode shape with lower computational cost. This technique shows pseudo modal Operating Deflections Shape(ODS) through bandpass filter and suggests time history Modal Assurance Criterion(MAC). Finally, mode shape could be estimated from pseudo modal ODS and time history MAC. Analytical simulations of vibration measurement were performed and the results with mode shape and computation time between representative SI method and proposed method were compared.

Keywords: modal assurance criterion, mode shape, operating deflection shape, system identification

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Authors: Rida Pervaiz, Bushra Allah Rakha, Muhammad Sajjad Ansari, Shamim Akhter, Kainat Waseem, Sumiyyah Zuha, Tooba Javed

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Ring-necked pheasant (Phasianus colchicus) belongs to order Galliformes and family Phasianidae. It has been recognized as the most hunted bird due to its attractive colorful appearance and meat. Loss of habitat and hunting pressure has caused population fluctuations in the native range. Under these circumstances, this species can be conserved by employing ex-situ in vitro conservation techniques. Captive breeding, in combination with semen cryobanking is the most appropriate option to conserve/propagate this species without deteriorating the genetic diversity. Cryopreservation protocols of adequate efficiency are necessary to establish semen cryobanking for a species. Therefore, present study was designed to devise an efficient extender for cryopreservation of ring-necked pheasant semen. For this purpose, a range of extenders (Beltsville Poultry, red fowl, Lake, EK, Tselutin Poultry and Chicken semen extenders) were evaluated for cryopreservation of ring-necked pheasant semen. Semen collected from 10 cocks, diluted in the Beltsville Poultry (BPSE), Red Fowl (RFE), Lake (LE), EK (EKE), Tselutin Poultry (TPE) and Chicken Semen (CSE) extenders and cryopreserved. Glycerol (10%) was added to semen at 4°C, equilibrated for 10 min, filled in 0.5 mL French straws, kept over liquid nitrogen vapors for 10 min, cryopreserved in LN2 and stored. Sperm motility (%), viability (%), live/dead ratio (%), plasma membrane (%) and DNA Integrity (%) were evaluated at post-dilution, post-cooling, post-equilibration and post-thawing stage of cryopreservation. Sperm motility (83.8 ± 3.1; 81.3 ± 3.8; 73.8 ± 2.4; 62.5 ± 1.4), viability (79.0 ± 1.7; 75.5 ± 1.6; 69.5 ± 2.3; 65.5 ± 2.4), live/dead ratio (80.5 ± 5.7; 77.3 ± 4.9; 76.0 ± 2.7; 68.3 ± 2.3), plasma membrane (74.5 ± 2.9; 73.8 ± 3.4; 71.3 ± 2.3; 75.0 ± 3.4) and DNA integrity (78.3 ± 1.7; 73.0 ± 1.2; 68.0 ± 2.0; 63.0 ± 2.5) at all four stages of cryopreservation were recorded higher (P < 0.05) in red fowl extender compared to all experimental extenders. It is concluded that red fowl extender is the best extender for cryopreservation of ring-necked pheasant semen and can be used in establishing cryobank for ex situ conservation.

Keywords: ring-necked pheasant; extenders; cryopreservation; semen quality; DNA integrity

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

Procedia PDF Downloads 323

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Lou Gargouri

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This paper examines how Fanny Cabon's solo performance, Gardiennes (2018) strategically crafts empathetic witnessing through the artist's vocal and physical embodiment of her female ancestors' testimonies, dramatizing the cyclical inheritance of reproductive trauma across generations. Drawing on affect theory and the concept of ethical co-presence, we argue that Cabon's raw voicing of illegal abortions, miscarriages, and abuse through her shape-shifting presence generates an intimate energy loop with the audience. This affective resonance catalyzes recognition of historical injustices, consecrating each singular experience while building collective solidarity. Central to Cabon's political efficacy is her transparent self-revelation through intimate impersonation, which fosters identification with diverse characters as interconnected subjects rather than objectified others. Her solo form transforms the isolation often associated with women's marginalization into radical inclusion, repositioning them from victims to empowered survivors. Comparative analysis with other contemporary works addressing abortion rights illuminates how Gardiennes subverts the traditional medical and clerical gazes that have long governed women's bodies. Ultimately, we contend Gardiennes models the potential of solo performance to harness empathy as a subversive political force. Cabon's theatrical alchemy circulates the effects of injustice through the ethical co-presence of performer and spectator, forging intersubjective connections that reframe marginalized groups traditionally objectified within dominant structures of patriarchal power. In dramatizing how the act of witnessing another's trauma can generate solidarity and galvanize resistance, Cabon's work demonstrates the role of embodied performance in catalyzing social change through the recuperation of women's voices and lived experiences. This paper thus aims to contribute to the emerging field of feminist solo performance criticism by illuminating how Cabon's innovative dramaturgy bridges the personal and the political. Her strategic mobilization of intimacy, identification, and co-presence offers a model for how the affective dynamics of autobiographical performance can be harnessed to confront gendered oppression and imagine more equitable futures. Gardiennes invites us to consider how the circulation of empathy through ethical spectatorship can foster the collective alliances necessary for advancing the unfinished project of women's liberation.

Keywords: gender and sexuality studies, solo performance, trauma studies, affect theory

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Rebecca Angeles

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This case study features the Kuehne + Nagel PharmaChain solution for ‘cold chain’ pharmaceutical and biologic product shipments with IOT-enabled features for shipment temperature and location tracking. Using the case study method and content analysis, this research project investigates the application of the structurational model of technology theory introduced by Orlikowski in order to interpret the firm’s entry and participation in the IOT-impelled marketplace.

Keywords: Internet of Things (IOT), radio frequency identification (RFID), structurational model of technology (Orlikowski), supply chain management

Procedia PDF Downloads 229

Authors: Henrik Prinzhorn, Peter Nyhuis, Johannes Wagner, Peter Burggräf, Torben Schmitz, Christina Reuter

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Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.

Keywords: assembly scheduling, large-scale products, make-to-order, optimization, rescheduling

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Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

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Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

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Authors: José Dinis-Carvalho, Levi Guimarães, Celina Leão, Rui Sousa, Rosa Eliza Vieira, Larissa Thomaz, Kelliane Guerreiro

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This research paper investigates the efficacy of waste identification diagrams (WIDs) as a tool for waste reduction and management within the Manaus Industrial Pole. The study focuses on assessing the practical application and effectiveness of WIDs in identifying, categorizing, and mitigating various forms of waste generated across industrial processes. Employing a mixed-methods approach, including a qualitative questionnaire applied to 5 companies and quantitative data analysis with SPSS statistical software, the research evaluates the implementation and impact of WIDs on waste reduction practices in select industries within the Manaus Industrial Pole. The findings contribute to understanding the utility of WIDs as a proactive strategy for waste management, offering insights into their potential for fostering sustainable practices and promoting environmental stewardship in industrial settings. The study also discusses challenges, best practices, and recommendations for optimizing the utilization of WIDs in industrial waste management, thereby addressing the broader implications for sustainable industrial development.

Keywords: waste identification diagram, value stream mapping, overall equipment effectiveness, lean manufacturing

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Authors: Juan Pablo Hervas-Perez, Jesus Guodemar-Perez, Montserrat Ruiz-Lopez, Elena Sonsoles Rodriguez-Lopez, Noemi Mayoral-Gonzalo, Eduardo Cimadevilla Fernandez-Pola, Mario Caballero-Corella

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Physiotherapy is a healthcare discipline that covers many fields of action within the recovery and prevention of health. Some are well known, but others, such as working with newborns and premature children are not so. Physical therapist functions are well defined, but the impression of the population is that there are other professionals who can develop them, and a large part are unknown. Objective: To evaluate the level of knowledge of the sample on the role of the physiotherapist in general, and more specifically in the neonatal intensive care (NICU) units, and estimate your level of notions on the development centered care (DCC). Method: A descriptive, transversal, observational and prospective study developed on a 125 participants' sample. Results: From the sample studied, 87.2% had already had contact with physiotherapy previously. An 80.9% believed that the physiotherapist intervention was decisive for the cure, and 84.0% would recommend physiotherapy treatment to others. Of the total surveyed, 98.0% felt that the physiotherapist is who should run the physiotherapeutic treatments, but shares with other professions 71.0% of votes. The field's best-known work is rehabilitation (94.0%); Neonatology is on the 4th place (66.0% of votes). Conclusions: Many areas of work of physical therapy are unknown to a big part of the population, including the own health workers. Less than half of the sample meets the DCC, and only 58% of the interviewed physiotherapists know them.

Keywords: functions of physiotherapist, neonatal intensive care, physiotherapy, prematurity

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Authors: Meriem Taleb, Ghania Tail, Fatma Zohra Kara, Brahim Djedouani, T. Moussa

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Forensic entomology is the use of insects and their arthropod relatives as silent witnesses to aid legal investigations by interpreting information concerning a death. The main purpose of forensic entomology is to establish the postmortem interval or PMI Postmortem interval is a matter of crucial importance in the investigations of homicide and other untimely deaths when the body found is after three days. Forensic entomology has grown immensely as a discipline in the past thirty years. In Algeria, forensic entomology was introduced in 2010 by the National Institute for Criminalistics and Criminology of the National Gendarmerie (NICC). However, all the work that has been done so far in this growing field in Algeria has been unknown at both the national and international levels. In this context, the aim of this paper is to describe the state of forensic entomology in Algeria. The Laboratory of Entomology of the NICC is the only one of its kind in Algeria. It started its activities in 2010, consisting of two specialists. The main missions of the laboratory are estimation of the PMI by the analysis of entomological evidence, and determination if the body was moved. Currently, the laboratory is performing different tasks such as the expert work required by investigators to estimate the PMI using the insects. The estimation is performed by the accumulated degree days method (ADD) in most of the cases except for those where the cadaver is in dry decay. To assure the quality of the entomological evidence, crime scene personnel are trained by the laboratory of Entomology of the NICC. Recently, undergraduate and graduate students have been studying carrion ecology and insect activity in different geographic locations of Algeria using rabbits and wild boar cadavers as animal models. The Laboratory of Entomology of the NICC has also been involved in some of these research projects. Entomotoxicology experiments are also conducted with the collaboration of the Toxicology Department of the NICC. By dint of hard work that has been performed by the Laboratory of Entomology of the NICC, official bodies have been adopting more and more the use of entomological evidence in criminal investigations in Algeria, which is commendable. It is important, therefore, that steps are taken to fill in the gaps in the knowledge necessary for entomological evidence to have a useful future in criminal investigations in Algeria.

Keywords: forensic entomology, corpse, insects, postmortem interval, expertise, Algeria

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Authors: M. Yakoubi, N. Belboukhari, A. Cheriti, K. Sekoum

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Launaea nudicaulis (L.) Hook.f. is a desert, spontaneous plant and endemic to northem Sahara, which belongs to the Asteraceae family. This species exists in the region of Bechar (Local name; El-Rghamma). In our knowledge, no work has been founded, except studies showing the antimicrobial and antifungal activity of methalonic extract of this plant. The present paper describes the chemical composition of the essential oil from Launaea nudicaulis and qualification of isolation and identification of some pure products by column chromatography. The essential oil from the aerial parts of Launaea nudicaulis (Asteraceae) was obtained by hydroditillation in 0.4% yield, led to isolation of four several new products. The isolation is made by column chromatography and followed by GC-IK and GC-MS analysis.

Keywords: Launaea nudicaulis, asteraceae, essential oil, column chromatography, GC-FID, GC-MS

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Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: Pedro H. S. Messetti, Mary L. G. S. Senna, Afonso R. Aquino

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Sustainability is a very important and heavily discussed subject, expanding through tourism as well. The study proposition was to collect data and present it to the competent bodies so they can mold their public politics to improve the conditions of the site. It was hypothesized that the lack of data is currently affecting the quality of life and the sustainable development of the site and the tourism. The research was held in Mateiros, a city in the state of Tocantins (TO)/Brasil, 275km far from the capital city Palmas, being one of the 8 cities that comprises the Jalapão region, an ecotourism and adventure tourism site as well as an environmental protection area (Jalapão State Park). Because of the concentration of tourists during the high season and several tourist attractions being around, the research took place in Mateiros. The methodological procedure had a script of theoretical construction and investigation of the deductive scientific method parameters through a case study in the Jalapão/TO/Brazil region, using it as a tool for a questionnaire given to the competent bodies in an interview system with the UN sustainability indexes as a base. In the three sustainable development scope: environmental, social and economic, the results indicated that the data presented by the interviewed were scarce or nonexistent. It shows that more research is necessary, providing the tools for the ones responsible to propose action plans to improve the site, strengthening the tourism and making it even more sustainable.

Keywords: Jalapão/Brazil state park, sustainable tourism, UN sustainability indexes

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Rajeshwari Balasubramanian, Margit Van Wessel, Nandini Deo

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The participation of women in local bodies witnessed a rise after the implementation of 73rd and 74th Amendments to the Indian Constitution which created quotas for women representatives. However, even when participation increased, it did not translate into meaningful contributions by women in local bodies. This led some civil society organisations (CSOs) to begin working with women panchayat representatives in various states to build their capacity for political participation. The focus of this paper is to study capacity building training by CSOs in Jharkhand. The paper maps how the training helps women elected representatives to negotiate their autonomy at multiple levels. The paper describes the capacity building program conducted by an international feminist organisation along with its seven local partners in Jharkhand. The central question that the study asks is: How does capacity building training by CSOs in Jharkhand impact the autonomy of elected women representatives? It uses a qualitative research methodology based on empirical data gathered through field visits in four districts of Jharkhand (Chatra, Hazaribagh, East Singhbum and Ranchi) where the program was implemented for three years. The study found that women elected representatives had to develop strategies to negotiate their choice to move out of their homes and attend the training conducted by CSOs. The ability to participate in the training programs itself was a significant achievement of personal autonomy for many women. The training provided them a platform to voice their opinion and appreciate their own value as panchayat leaders. This realization allowed them to negotiate their presence and a space for themselves in Gram panchayats. A Foucauldian approach to analyze capacity building workshops might lead us to see them as systems in which CSOs impose a form of governmentality on rural elected representatives. Instead, what we see here is a much more complex negotiation of agency in which the CSO creates spaces and practices that allow women to achieve their own forms of autonomy. The study concludes that the impact of the training on the autonomy of these women is based on their everyday negotiations of time, space and mobility. Autonomy for these elected women representatives is also contextual and relative, as they seem to realize it during the training process. The training allows the women to not only negotiate their participation in panchayats but also challenge everyday practices that are rooted in patriarchy.

Keywords: autonomy, feminist organization, local bodies, political participation

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Authors: Rabiaal Adawiyah Shazali, Corina Joseph

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The disclosure of Intellectual Capital (IC) information is getting more vital in today’s era of a knowledge-based economy. Companies are advised by accounting bodies to enhance IC disclosure which complements the conventional financial disclosures. There are no accounting standards for Intellectual Capital Disclosure (ICD), therefore the disclosure is entirely voluntary. Hence, this study aims to investigate the extent of ICD and to examine the relationship between corporate governance and ICD in Malaysia. This study employed content analysis of 100 annual reports by the top 100 public listed companies in Malaysia during 2012. The uniqueness of this study lies on its underpinning theory used where it applies the institutional isomorphism theory to support the effect of the attributes of corporate governance towards ICD. In order to achieve the stated objective, multiple regression analysis were employed to conduct this study. From the descriptive statistics, it was concluded that public listed companies in Malaysia have increased their awareness towards the importance of ICD. Furthermore, results from the multiple regression analysis confirmed that corporate governance affects the company’s ICD where the frequency of audit committee meetings and the board size has positively influenced the level of ICD in companies. Findings from this study would provide an incentive for companies in Malaysia to enhance the disclosure of IC. In addition, this study would assist Bursa Malaysia and other regulatory bodies to come up with a proper guideline for the disclosure of IC.

Keywords: annual report, content analysis, corporate governance, intellectual capital disclosure

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Authors: Thuy Hanh Nguyen Thi

Abstract:

Since 1940, existentialism has penetrated into China and continued to profoundly influence contemporary Chinese literature. By the method of deep reading and text analysis, this article analyzes the existential feeling in Yan Lianke’s novels through various aspects: the Sisyphus senses, the narrative rationalization and the viewpoint of the dead. In addition to pointing out the characteristics of the existential sensation in the writer’s novels, the analysis of the article also provides an insight into the nature and depth of contemporary Chinese society.

Keywords: Yan Lianke, existentialism, the existential feeling, contemporary Chinese literature

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Authors: Hongmin Deng, Qionghua Wang

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A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: chaos encryption, logistic map, pseudo-random sequence, RFID

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Authors: Lavanya Srinivasan

Abstract:

Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: H. Imad, Y. Cheah, O. Aamera

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The aims of this research are to study the mitochondrial non-coding region by using the Sanger sequencing technique and establish the degree of variation characteristics of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. A portion of a non-coding region encompassing positions 37 to 340 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and detected by using the ABI 3730xL DNA Analyzer. New polymorphic positions 57, 63, and 101 are described may in future be suitable sources for identification purpose. The data obtained can be used to identify variable nucleotide positions characterized by frequent occurrence most promising for identification variants.

Keywords: encompassing nucleotide positions 37 to 340, HVII, Iraq, mitochondrial DNA, polymorphism, frequency

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Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* algorithm, autonomous turrets, high-dimensional C-space, manifold C-space, point clouds

Procedia PDF Downloads 135