Search results for: human detection and identification

Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

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The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

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Authors: Hasanzadeh Mehran

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The Cyrus Cylinder, which is a baked clay tablet, was written in 539 BC by order of the Achaemenid king Cyrus. This clay tablet contains orders and is considered a historical document of the humanitarian behaviour of the victorious army during the conquest of Babylon. Some believe that these laws are the first declaration of human rights in the ancient world. After the conquest of Babylon, Cyrus created laws that had never been seen anywhere in history. For this reason, in this article it has been tried to mention the human aspects and the reasons and grounds for the formation of such laws at that time. The origin of the creation of these progressive and humanitarian laws in the Cyrus cylinder should be sought in the cultural roots of civilization and his social and individual teachings.

Keywords: Iran, cyrus, cyrus cylinder, human rights

Procedia PDF Downloads 96

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Marwa Ragab, Eman El-Kimary

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Chiral separation and analysis of omeprazole and naproxen enantiomers in tablets were achieved using high-performance liquid chromatographic method with diode array detection (HPLC-DAD). Kromasil Cellucoat chiral column was used as a stationary phase for separation and the eluting solvent consisted of hexane, isopropanol and trifluoroacetic acid in a ratio of: 90, 9.9 and 0.1, respectively. The chromatographic system was suitable for the enantiomeric separation and analysis of active isomers of the drugs. Resolution values of 2.17 and 3.84 were obtained after optimization of the chromatographic conditions for omeprazole and naproxen isomers, respectively. The determination of S-isomers of each drug in their dosage form was fully validated.

Keywords: chiral analysis, esomeprazole, S-Naproxen, HPLC-DAD

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Authors: Daria Beziakina, Elena Bulgakova

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The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers. The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language. The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

Procedia PDF Downloads 347

Authors: Djebbar Atmani, Aghiles Karim Aissat, Nadjet Debbache-Benaida, Nassima Chaher-Bazizi, Dina Atmani-Kilani, Meriem Rahmani-Berboucha, Naima Saidene, Malika Benloukil, Lila Azib

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Medicinal plants are believed to be an important source for the discovery of potential antioxidant, anti-inflammatory and anti-diabetic substances. The present study was designed to investigate the neuroprotective, anti-inflammatory, anti-diabetic and anti-hyperuricemic potential of Pistacia lentiscus, as well as the identification of active compounds. The antioxidant potential of plant extracts against known radicals was measured using various standard in vitro methods. Anti-inflammatory activity was determined using the paw edema model in mice and by measuring the secretion of the pro-inflammatory cytokine, whereas the anti-diabetic effect was assessed in vivo on streptozotocin-induced diabetic rats and in vitro by inhibition of alpha-amylase. The anti-hyperuricemic activity was evaluated using the xanthine oxidase assay, whereas neuroprotective activity was investigated using an Aluminum-induced toxicity test. Pistacia lentiscus extracts and fractions exhibited high scavenging capacity against DPPH, NO. and ABTS+ radicals in a dose-dependent manner and restored blood glucose levels, in vivo, to normal values, in agreement with the in vitro anti-diabetic effect. Oral administration of plant extracts significantly decreased carrageenan-induced mice paw oedema, similar to the standard drug, diclofenac, was effective in reducing IL-1β levels in cell culture and induced a significant increase in urinary volume in mice, associated to a promising anti-hyperuricemic activity. Plant extracts showed good neuroprotection and restoration of cognitive functions in mice. HPLC-MS and NMR analyses allowed the identification of known and new phenolic compounds that could be responsible for the observed activities. Therefore, Pistacia lentiscus could be beneficial in the treatment of inflammatory conditions and diabetes complications and the enhancement of cognitive functions.

Keywords: Pistacia lentiscus, anti-inflammatory, antidiabetic, flavanols, neuroprotective

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Authors: Ankur Dixit, Hiroaki Wagatsuma

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The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

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Authors: Mohsen Nouraei, Mohammad Molavi

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Muslim scholars for a long time have tried to prove the necessity of prophecy through the Qur'an verses, Hadith's concepts, and rational arguments. According to them, the human being cannot find his welfare way based on wisdom only. They emphasize that divine teaching of the prophets accompanied by wisdom (reason) helps people to find the best way of life and consequently they achieve perfection. In contrast, some believe that mentioned necessity is helpful for primitive and ancient societies, and, matured man in the modern era has flourished his wisdom and reached the peak of maturity. Hence, the modern human can recognize good and evil rely on the individual and social wisdom and as a result they can reach to the perfection without revelation and prophetic teaching. The essay via descriptive-analytical method has attempted to analyze and critic this thought through the study of Mottahari's works as a modern prominent scholars. Findings show that AyatuAllah Mottahari believes that not only modern human intellectual development is not needless of prophecy, but also they need religion and revelation teaching exactly like primitive and ancient societies. Wisdom inherent limitations common between primitive and modern human are the main reason of AyatuAllah Mottahari.

Keywords: wisdom, modernity, prophecy, AyatuAllah Mottahari

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: Delphine Duval, Morgan Mangeas, Charlie Huveneers, Adam Barnett, Laurent Vigliola

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The global number of shark bites has increased over the past four decades with, however, high regional variability both in space and time. A systematic review, aligned with the 2020 PRISMA guidelines, explored the peer-reviewed literature published between 1960 and 2023 to identify factors potentially explaining trends in human-shark interactions. Results revealed that variations in the frequency of human-shark interactions could be explained by a plethora of factors, including changes in prey availability, environmental conditions, human and shark population density and behavior, as well as habitat destruction. However, to our best knowledge, only five studies have conducted statistical assessments of the relative contribution of these factors. The increased number in human-shark interactions and the frequent clusters of shark bites within short timeframes offer opportunities to test the causative factors that may explain trends in unprovoked shark bites. it study aims to evaluate the impact of marine protected areas (MPAs) on the number of human-shark interactions, using data from the Global Shark Attack File and the World Database on Protected Areas. Results indicate contrasting effects of MPAs at different spatial scales. Enhancing our understanding of the factors contributing to shark bites is essential for improving risk reduction policies for humans and conservation plans for shark populations.

Keywords: unprovoked shark interactions, marine protected areas, attack risk, human-wildlife interaction

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: S. Sokel, M. Kale

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Norovirus (NoV) infection is effective and contagious in humans and many animals such as calves, pigs, dogs, cats, monkeys. There is not enough evidence about the zoonotic transmission of NoV between humans and animals. However, the fact that contamination of foods and environment by animal/human waste happens in indirect way leads to consideration of the agent as a zoonotic character. In our study, we aim to search the presence of NoV infection, which is a major public health problem, in possessed dogs showing diarrhea symptoms, to detect its genotype and to study nutrition and life conditions. We searched the existence of human NoV GI, GII and GIV in the stool of 128 pet dogs in Burdur Province with diarrhoea in various sex, age and breed by using Real-Time PCR method. Human NoV GII was found in only 5 of the 128 dog stool samples (3.91%). In the study, it was determined that the owners of the dogs with NoV GII are middle aged or elderly people most of whom are male and that there were no children in their houses. As these dogs are treated like the owner’s child, it is assumed that they could be transmitted with NoV GII as a result of close interaction with their owner.

Keywords: dog, human, norovirus, Real-Time PCR, stool

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Authors: Andrei Nastas, Sergiu Cernomopret

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This research addresses trafficking in human beings, in terms of the active subject and the victim of this crime, through the prism of national and international regulations in material and procedural criminal matters. For the correlative approach of both mentioned aspects, the active subject and the victim of trafficking in human beings, the research addresses both its constituent elements and the way to prevent and combat this phenomenon through criminal proceedings. As follows, trafficking in human beings, from a material criminal point of view, involves two subjects of this crime (active subject - offender and passive subject - victim), while their procedural status differs depending on the case (victim or injured party). The result of the research highlights some clarifications, which find a theoretical-practical basis in the legal provisions, the specialized doctrine, and the judicial practice.

Keywords: victim, active subject, abuse, injured party, crime

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Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Amit Verma, Pardeep Kaur

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In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

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Authors: Hyo-Su Lim, Ye-Eun Song, Eun-Bi Lee, Sang-Yoon Lee, Young-Il Seo, Jin-Pyo Kim, Nam-Kyu Park

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If we analogize any physical external force given to victims in many crimes including violence, it would be possible not only to presume mutual action between victims and suspects, but to make a deduction of more various facts in cases. Therefore, the aim of this study is to identify criminal tools through secretion on clothes by using amino acid reagents such as Ninhydrin, DFO(1,8-dizafluoren-9-one), 1,2 – IND (1,2-indanedione) which are reacting to skin secretion. For more effective collecting condition, porcine skin which is physiologically similar to human was used. Although there were little differences of shape identification according to sensitivity, amino acid reagents were able to identify the fist, foot, and baseball bat. Furthermore, we conducted the experiments for developmental variations through change over time setting up 5-weeks period including first damage as variation factor, and developing materials in each action through certain reagents. Specimen level of development depending on change over time was identified. As a result, each of initial level of development was seen no changes.

Keywords: hit marks, amino acid reagents, porcine skin, criminal tool

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Authors: Ketan Naik, P. H. Bhathawala

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The purpose of this work is to develop a mathematical model of Human Cardiovascular System using lumped parameter method. The model is divided in three parts: Systemic Circulation, Pulmonary Circulation and the Heart. The established mathematical model has been simulated by MATLAB software. The innovation of this study is in describing the system based on the vessel diameters and simulating mathematical equations with active electrical elements. Terminology of human physical body and required physical data like vessel’s radius, thickness etc., which are required to calculate circuit parameters like resistance, inductance and capacitance, are proceeds from well-known medical books. The developed model is useful to understand the anatomic of human cardiovascular system and related syndromes. The model is deal with vessel’s pressure and blood flow at certain time.

Keywords: cardiovascular system, lumped parameter method, mathematical modeling, simulation

Procedia PDF Downloads 333

Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

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Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Lixin Tian, Wei Xue

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Many jobs in society go underground, such as mine mining, tunnel construction and subways, which are vital to the development of society. Once accidents occur in these places, the interruption of traditional wired communication is not conducive to the development of rescue work. In order to realize the positioning, early warning and command functions of underground personnel and improve rescue efficiency, it is necessary to develop and design an emergency ground communication system. It is easy to be subjected to narrowband interference when performing conventional underground communication. Spreading communication can be used for this problem. However, general spread spectrum methods such as direct spread communication are inefficient, so it is proposed to use parallel combined spread spectrum (PCSS) communication to improve efficiency. The PCSS communication not only has the anti-interference ability and the good concealment of the traditional spread spectrum system, but also has a relatively high frequency band utilization rate and a strong information transmission capability. So, this technology has been widely used in practice. This paper presents a PCSS communication model-multiple detection parallel combined spread spectrum (MDPCSS) communication system. In this paper, the principle of MDPCSS communication system is described, that is, the sequence at the transmitting end is processed in blocks and cyclically shifted to facilitate multiple detection at the receiving end. The block diagrams of the transmitter and receiver of the MDPCSS communication system are introduced. At the same time, the calculation formula of the system bit error rate (BER) is introduced, and the simulation and analysis of the BER of the system are completed. By comparing with the common parallel PCSS communication, we can draw a conclusion that it is indeed possible to reduce the BER and improve the system performance. Furthermore, the influence of different pseudo-code lengths selected on the system BER is simulated and analyzed, and the conclusion is that the larger the pseudo-code length is, the smaller the system error rate is.

Keywords: cyclic shift, multiple detection, parallel combined spread spectrum, PN code

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Authors: Hideyuki Shintani, Ichiro Koshijima

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In Cyber Physical System (CPS), if there are a large number of persons in the process, a role of person in CPS might be different comparing with the one-man system. It is also necessary to consider how Human-in-The-Loop Cyber Physical Systems (HiTLCPS) ensure safety of each person in the loop process. In this paper, the authors discuss a system safety framework with an illustrative example with STAMP model to clarify what point for safety should be considered and what role of person in the should have.

Keywords: cyber-physical-system, human-in-the-loop, safety, STAMP model

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Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

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The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: binary segmentation, change point, exponentialLomax distribution, information criterion

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Authors: Bita Kharazi

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The purpose of this research was to investigate the impact of innovations in human resource practices, innovation capabilities, and competitive advantage on company performance. This research was applied in terms of purpose and in terms of method, it was descriptive research of correlation type. The statistical population of this research was all the employees of Zar Industrial and Research Group. The sampling method was available in this research, and Cochran's formula was used to determine the statistical sample size. A standard questionnaire was used to collect information in this research, and SPSS software and simultaneous regression statistical tests were used to analyze the data. Based on the findings of the present research, it was found that the components of creativity in human resource practices, innovation capability, and competitive advantage have a significant impact on the company's performance.

Keywords: human resource management, innovation, competitive advantage, company performance

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Authors: Desmond F. Bellamy

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Discourses about animal rights usually assume an ontological abyss between human and animal. This supposition of non-animality allows us to utilise and exploit non-humans, particularly those with commercial value, with little regard for their rights or interests. We can and do confine them, inflict painful treatments such as castration and branding, and slaughter them at an age determined only by financial considerations. This paper explores the way images and texts depicting human cannibalism reflect this deprivation of rights back onto our species and examines how this offers new perspectives on our granting or withholding of rights to farmed animals. The animals we eat – sheep, pigs, cows, chickens and a small handful of other species – are during processing de-animalised, turned into commodities, and made unrecognisable as formerly living beings. To do the same to a human requires the cannibal to enact another step – humans must first be considered as animals before they can be commodified or de-animalised. Different iterations of cannibalism in a selection of fiction and non-fiction texts will be considered: survivalism (necessitated by catastrophe or dystopian social collapse), the primitive savage of colonial discourses, and the inhuman psychopath. Each type of cannibalism shows alternative ways humans can be animalised and thereby dispossessed of both their human and animal rights. Human rights, summarised in the UN Universal Declaration of Human Rights as ‘life, liberty, and security of person’ are stubbornly denied to many humans, and are refused to virtually all farmed non-humans. How might this paradigm be transformed by seeing the animal victim replaced by an animalised human? People are fascinated as well as repulsed by cannibalism, as demonstrated by the upsurge of films on the subject in the last few decades. Cannibalism is, at its most basic, about envisaging and treating humans as objects: meat. It is on the dinner plate that the abyss between human and ‘animal’ is most challenged. We grasp at a conscious level that we are a species of animal and may become, if in the wrong place (e.g., shark-infested water), ‘just food’. Culturally, however, strong traditions insist that humans are much more than ‘just meat’ and deserve a better fate than torment and death. The billions of animals on death row awaiting human consumption would ask the same if they could. Depictions of cannibalism demonstrate in graphic ways that humans are animals, made of meat and that we can also be butchered and eaten. These depictions of us as having the same fleshiness as non-human animals reminds us that they have the same capacities for pain and pleasure as we do. Depictions of cannibalism, therefore, unconsciously aid in deconstructing the human/animal binary and give a unique glimpse into the often unnoticed repudiation of animal rights.

Keywords: animal rights, cannibalism, human/animal binary, objectification

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Authors: M. Bartal

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A large empirical evidence points to sizable lifetime earnings losses associated with the displacement of tenured workers. The causes of these losses are still not well-understood. Existing explanations are heavily based on human capital depreciation during non-employment spells. In this paper, a new avenue is explored. Evidence on the role of household liquidity constraints in accounting for the persistence of post-displacement earning losses is provided based on SIPP data. Then, a directed search and matching model with endogenous human capital and wealth accumulation is introduced. The model is computationally tractable thanks to its block-recursive structure and highlights a non-trivial, yet intuitive, interaction between wealth and human capital. Constrained workers tend to accept jobs with low firm-sponsored training because the latter are (endogenously) easier to find. This new channel provides a plausible explanation for why young (highly constrained) workers suffer persistent scars after displacement. Finally, the model is calibrated on US data to show that the interplay between wealth and human capital is crucial to replicate the observed lifecycle pattern of earning losses. JEL— E21, E24, J24, J63.

Keywords: directed search, human capital accumulation, job displacement, wealth accumulation

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Authors: Juan Carlos Rubio Romero, Francico Salguero Caparros, Virginia Herrera-Pérez

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No one is in the slightest doubt about the high levels of risk involved in work in the construction industry. They are even higher in structural construction work. The Critical Decision Method (CDM) is a semi-structured interview technique that uses cognitive tests to identify the different disturbances that workers have to deal with in their work activity. At present, the vision of safety focused on daily performance and things that go well for safety and health management is facing the new paradigm known as Resilience Engineering. The aim of this study has been to describe the variability in formwork labour on concrete structures in the construction industry and, from there, to find out the resilient attitude of workers to unexpected events that they have experienced during their working lives. For this purpose, a series of semi-structured interviews were carried out with construction employees with extensive experience in formwork labour in Spain by applying the Critical Decision Method. This work has been the first application of the Critical Decision Method in the field of construction and, more specifically, in the execution of structures. The results obtained show that situations categorised as unthought-of are identified to a greater extent than potentially unexpected situations. The identification during these interviews of both expected and unexpected events provides insight into the critical decisions made and actions taken to improve resilience in daily practice in this construction work. From this study, it is clear that it is essential to gain more knowledge about the nature of the human cognitive process in work situations within complex socio-technical systems such as construction sites. This could lead to a more effective design of workplaces in the search for improved human performance.

Keywords: resilience engineering, construction industry, unthought-of situations, critical decision method

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Authors: Christa L. Arnold, Margaret C. Stewart

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This research shares the results of an exploratory study examining Statement Analysis (SA) to detect deception in online truthful and untruthful social media posts. Applying a Law Enforcement methodology SA, used in criminal interview statements, this research analyzes what is stated to assist in evaluating written deceptive information. Preliminary findings reveal qualitative and quantitative nuances for SA in online deception detection and uncover insights regarding digital deceptive behavior. Thus far, findings reveal truthful statements tend to differ from untruthful statements in both content and quality.

Keywords: deception detection, online deception, social media content, statement analysis

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Authors: Dona Grace Jeyaseeli

Abstract:

Water quality conditions in a pond are controlled by both natural processes and human influences. Natural factors such as the source of the pond water and the types of rock and soil in the pond watershed will influence some water quality characteristics. These factors are difficult to control but usually cause few problems. Instead, most serious water quality problems originate from land uses or other activities near or in the pond. The effects of these activities can often be minimized through proper management and early detection of problems through testing. In the present study a survey of three ponds in Coimbatore city, Tamilnadu, India were analyzed and found that water quality problems in their ponds, ranging from muddy water to fish kills. Unfortunately, most pond owners have never tested their ponds, and water quality problems are usually only detected after they cause a problem. Hence the present study discusses some common water quality parameters that may cause problems in ponds and how to detect through testing for better management of pond.

Keywords: water quality, pond, test, problem

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