Search results for: dynamic capability approach

Authors: Polina Prokopovich

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Despite the well-established dependence of cartilage mechanical properties on the frequency of the applied load, most research in the field is carried out in either load-free or constant load conditions because of the complexity of the equipment required for the determination of time-dependent properties. These simpler analyses provide a limited representation of cartilage properties thus greatly reducing the impact of the information gathered hindering the understanding of the mechanisms involved in this tissue replacement, development and pathology. More complex techniques could represent better investigative methods, but their uptake in cartilage research is limited by the highly specialised training required and cost of the equipment. There is, therefore, a clear need for alternative experimental approaches to cartilage testing to be deployed in research and clinical settings using more user-friendly and financial accessible devices. Frequency dependent material properties can be determined through rheometry that is an easy to use requiring a relatively inexpensive device; we present how a commercial rheometer can be adapted to determine the viscoelastic properties of articular cartilage. Frequency-sweep tests were run at various applied normal loads on immature, mature and trypsinased (as model of osteoarthritis) cartilage samples to determine the dynamic shear moduli (G*, G′ G″) of the tissues. Moduli increased with increasing frequency and applied load; mature cartilage had generally the highest moduli and GAG depleted samples the lowest. Hydraulic permeability (KH) was estimated from the rheological data and decreased with applied load; GAG depleted cartilage exhibited higher hydraulic permeability than either immature or mature tissues. The rheometer-based methodology developed was validated by the close comparison of the rheometer-obtained cartilage characteristics (G*, G′, G″, KH) with results obtained with more complex testing techniques available in literature. Rheometry is relatively simpler and does not require highly capital intensive machinery and staff training is more accessible; thus the use of a rheometer would represent a cost-effective approach for the determination of frequency-dependent properties of cartilage for more comprehensive and impactful results for both healthcare professional and R&D.

Keywords: tissue, rheometer, biomaterial, cartilage

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Authors: Amit Gupta, Deepak Juneja, Sorabh Gupta

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This paper presents a model based on distance based approach (DBA) method employed for evaluation, selection, and ranking of replenishment policies for a single location inventory, which hitherto not developed in the literature. This work recognizes the significance of the selection problem, identifies the selection criteria, the relative importance of selection criteria for this research problem. The developed model is capable of comparing any number of alternate inventory policies for various selection criteria where cardinal values are assigned as a rating to alternate inventory polices for selection criteria and weights of selection criteria. The illustrated example demonstrates the model and presents the result in terms of ranking of replenishment policies.

Keywords: DBA, ranking, replenishment policies, selection criteria

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Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Pavel Psota, Vít Lédl, Jan Václavík, Roman Doleček, Pavel Mokrý, Petr Vojtíšek

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This paper presents advanced time average digital holography by means of frequency shift and phase modulation. This technique can measure amplitudes of vibrations at ultimate dynamic range while the amplitude distribution evaluation is done independently in every pixel. The main focus of the paper is to gain insight into behavior of the method at low amplitudes of vibrations. In order to reach that, a set of experiments was performed. Results of the experiments together with novel noise suppression show the limit of the method to be below 0.1 nm.

Keywords: acusto-optical modulator, digital holography, low amplitudes, vibrometry

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

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The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: cytokine, saliva, attention deficit hyperactivity disorder, child

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Authors: Naum Simanovsky MD, Michael Zaidman MD, Vladimir Goldman MD.

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105 plain AP radiographs of normal adult pelvises (210 hips) were evaluated. Different measurements of normal and dysplastic hip joints in 45 patients were analyzed. Attempt was made to establish reproducible, easy applicable in practice approach for evaluation and follow up of patients with hip dysplasia. The youngest of our patients was 11 years and the oldest was 47 years. Only one of our patients needed conversion to total hip replacement (THR) during ten years of follow-up. It was emphasized that selected set of measurements was built for purpose to serve, especially those who’s scheduled or undergone PAO. This approach was based on concept of acetabulum-femoral head complex and importance of reliable reference points of measurements. Comparative analysis of measured parameters between normal and dysplastic hips was performed. Among 10 selected parameters, we use already well established such as lateral center edge angle and head extrusion index, but to serve specific group of patients with PAO, new parameters were considered such as complex lateralization and complex proximal migration. By our opinion proposed approach is easy applicable in busy clinical practice, satisfactorily delineate hip pathology and give to surgeon who’s going to perform PAO guidelines in condensed form. It is also useful tools for postoperative follow up after PAO.

Keywords: periacetabular osteotomy, plain radiograph’s measurements, adolescents, adult

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Authors: Olga A. Shvetsova

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The paper contains the different issues of competence management in industrial companies. The theoretical bases of human resources management and practical issues of innovative enterprises’ competitiveness are considered. The research is focused on the modern industrial enterprise changes management problems; it focuses on the effective personnel management of industrial enterprises on the basis of competence approach. The influence of organizational changes on the competence development is discussed. The need for development of the new technologies is mentioned, proposal is based on competence-based approach in personnel management including in the conditions of carrying out organizational changes; methods of acquisition and development of missing key professional competences are discussed; importance of key competencies in forming competitive advantage of the organization is mentioned.

Keywords: competence model, core competencies, development of industrial company, organizational changes, competitiveness

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Authors: Miguel A. Borrella, Ana P. Fanjul, Suca Munoz, Liliana Herrera

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This paper evaluates the impact of LEADER, a remarkable Community-Led Local Development (CLLD) approach of the European Program for Rural Development applied to rural municipalities of Spain in 2018 and 2019. Using a difference-in-difference estimation strategy and a newly-constructed database, results show that aided municipalities have significantly lower unemployment levels than non-aided municipalities. Results are significant for the decrease in unemployment for both women and people younger than 25 years old, two of the target groups of the policy. Nevertheless, they are larger for male and older workers. Therefore, findings suggest that LEADER 2017-2018 was successful in reducing unemployment in rural areas.

Keywords: community-led local development, ex-post evaluation, LEADER, rural development

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: S. Zhuiykov, Z. Wei

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Conformal defect-free two-dimensional (2D) WO₃ and TiO₂ semiconductors have been developed by the atomic layer deposition (ALD) technique on wafer scale with unique approach to the thickness control with precision of ± 10% from the monolayer of nanomaterial (less than 1.0 nm thick) to the nano-layered 2D structures with thickness of ~3.0-7.0 nm. Developed 2D nanostructures exhibited unique, distinguishable properties at nanoscale compare to their thicker counterparts. Specifically, 2D TiO₂-Au bilayer demonstrated improved photocatalytic degradation of palmitic acid under UV and visible light illumination. Improved functional capabilities of 2D semiconductors would be advantageous to various environmental, nano-energy and bio-sensing applications. The ALD-enabled approach is proven to be versatile, scalable and applicable to the broader range of 2D semiconductors.

Keywords: two-dimensional (2D) semiconductors, ALD, WO₃, TiO₂, wafer scale

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Authors: Vojtěch Gybas, Libor Klubal, Kateřina Kostolányová

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Nowadays, mobile touch technologies, such as tablets, are an integral part of teaching and learning in many special elementary schools. Many special education teachers tend to choose an iPad tablet with iOS. The reason is simple; the iPad has a function for pupils with special educational needs. If we decide to use tablets in teaching, in general, first we should try to stimulate the cognitive abilities of the pupil at the highest level, while holding the pupil’s attention on the task, when working with the device. This paper will describe how student attention can be increased by eliminating the working environment of selected applications, while using iPads with pupils in a special elementary school. Assisted function approach is highly effective at eliminating unwanted touching by a pupil when working on the desktop iPad, thus actively increasing the pupil´s attention while working on specific educational applications. During the various stages of the action, the research was conducted via data collection and interpretation. After a phase of gaining results and ideas for practice and actions, we carried out the check measurement, this time using the tool-assisted approach. In both cases, the pupils worked in the Math Board application and the resulting differences were evident.

Keywords: special elementary school, a mobile touch device, iPad, attention, Math Board

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Raymond K. Dziwornu

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Lending rate of agriculture loan has persistently been high and attributed to risk in the sector. This study examined how food inflation and agriculture lending rate react to each other in Ghana using vector autoregressive approach. Quarterly data from 2006 to 2018 was obtained from the Bank of Ghana quarterly bulletin and the Ghana Statistical Service reports. The study found that a positive standard deviation shock to food inflation causes lending rate of agriculture loan to react negatively in the short run, but positively and steadily in the long run. This suggests the need to direct appropriate policy measures to reduce food inflation and consequently, the cost of credit to the agricultural sector for its growth.

Keywords: food inflation, agriculture, lending rate, vector autoregressive, Ghana

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Authors: Ayomide Oyedele

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In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

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Authors: Kyria Rebeca Finardi

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The study discusses the role of foreign languages in general and of English in particular in the process of internationalization of higher education (IHE), defined as the intentional integration of an international, intercultural or global dimension in the purpose, function or offer of higher education. The study is bibliographical and offers a brief outline of the current political, economic and educational scenarios in Brazil, before discussing some possibilities and challenges for the development of multilingualism and IHE there. The theoretical background includes a review of Brazilian language and internationalization policies. The review and discussion concludes that the use of the Content and Language Integrated Learning (CLIL) approach and the Intercomprehension approach to foreign language teaching/learning are relevant alternatives to foster multilingualism in that context.

Keywords: Brazil, higher education, internationalization, multilingualism

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

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Authors: Rik van Leeuwen, Ger Koole

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Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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Authors: Mostafa Dastori, Sirus Mohammadi

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While plug-in electric vehicles (PEVs) potentially have the capability to fulfill the energy storage needs of the electric grid, the degradation on the battery during this operation makes it less preferable by the auto manufacturers and consumers. On the other hand, the on-board chargers can also supply energy storage system applications such as reactive power compensation, voltage regulation, and power factor correction without the need of engaging the battery with the grid and thereby preserving its lifetime. It presents the design motives of single-phase on-board chargers in detail and makes a classification of the chargers based on their future vehicle-to-grid usage. The pros and cons of each different ac–dc topology are discussed to shed light on their suit- ability for reactive power support. This paper also presents and analyzes the differences between charging-only operation and capacitive reactive power operation that results in increased demand from the dc-link capacitor (more charge/discharge cycles and in- creased second harmonic ripple current). Moreover, battery state of charge is spared from losses during reactive power operation, but converter output power must be limited below its rated power rating to have the same stress on the dc-link capacitor.

Keywords: energy storage system, battery unit, cost, optimal sizing, plug-in electric vehicles (PEVs), smart grid

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Authors: Babak Mirzashahi, Arvin Najafi, Pejman Mansouri, Mahmoud Farzan

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Background: The most effective treatment of posterior cruciate ligament (PCL) tears and the consequence of untreated PCL injuries remain controversial. Objectives: The aim of this study is to assess outcomes of fixation of tibial posterior cruciate ligament (PCL) avulsion fractures via a modified technique. Patients and Methods: From January, 2009 to March, 2012, there were 45 cases of PCL tibial avulsion fractures that were referred to our hospital and were managed through a modified open posterior approach. Fixation of Tibial PCL avulsion fractures were fixed by means of a lag screw and washer placed through our modified open posterior approach. Range of motion was begun on the first postoperative day. Clinical stability, range of motion, gastrocnemius muscle strength, radiographic investigation, and patient’s overall quality of life was analyzed at final follow up visit. Results: The average of overall musculoskeletal functional evaluation scores was 15 (range 3–35). All patients achieved union of their fracture and had clinically stable knees at the latest follow-up. The mean preoperative Lysholm score for 15 knees was 62 ± 8 (range, 50-75); the mean postoperative Lysholm score was 92± 7 (range, 75-101). A significant difference in Lysholm scores between preoperative and final follow-up evaluations was found (P < .05). At first-year follow-up, 42 (93%) patients revealed a difference of less than 10 mm in thigh circumference between their injured and healthy knees. Conclusions: The management of displaced large PCL avulsion fractures with placement of a cancellous lag screw with washer by means of the modified open posterior approach leads to satisfactory clinical, radiographic, and functional results and reduces the operation time and less blood loss. Level of evidence: IV.

Keywords: posterior cruciate ligament, tibial fracture, lysholm knee score, patient outcome assessment

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Authors: Neelam Kadyan

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Global environmental change is happening at an alarming rate in the present world. Floods, Tsunamis’, Avalanches, Change in Weather patterns, Rise in sea temperature, Landslides, are only few evidences of this change. To regulate such alarming growth of global change in environment certain regulatory system or mechanism is required. Nuisance,negligence,absolute liability,strict liability and trespass are some of the effective common law principles which are helpful in environmental problems. What we need today is sufficient law and adequate machinery to enforce the legal standards. Without law environmental standards cannot be enforced and once again there is need to adopt the common law approach in solving the problem of environmental change as through this approach the affected person can get compensation and as the same time it puts check on wrongdoer.

Keywords: global environmental problems, nuisance, negligence, trespass, strict liability, absolute liability

Procedia PDF Downloads 566

Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: Marzie Shahini, Rasoul Mirghaderi

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This paper describes collapse assessments of a steel moment-frame high-rise tower with setback irregularity, designed per the 2010 ASCE7 code, under spectral-matched ground motion records. To estimate a safety margin against life-threatening collapse, an analytical model of the tower is subjected to a suite of ground motions with incremental intensities from maximum considered earthquake hazard level to the incipient collapse level. Capability of the structural system to collapse prevention is evaluated based on the similar methodology reported in FEMA P695. Structural performance parameters in terms of maximum/mean inter-story drift ratios, residual drift ratios, and maximum plastic hinge rotations are also compared to the acceptance criteria recommended by the TBI Guidelines. The results demonstrate that the structural system satisfactorily safeguards the building against collapse. Moreover, for this tower, the code-specified requirements in ASCE7-10 are reasonably adequate to satisfy seismic performance criteria developed in the TBI Guidelines for the maximum considered earthquake hazard level.

Keywords: high-rise buildings, set back, residual drift, seismic performance

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Authors: Rashi Mahato

Abstract:

Talent management represents an organization’s effort to attract, develop and retain highly skilled and valuable employees. The goal is to have people with capabilities and commitment needed for current and future organizational success. The organizational talent pool is its managerial talent referred to as leadership pipeline. It is managed through various systems and processes to help the organization source, reward, evaluate, develop and move employees into various functions and roles. The pipeline bends, turns, and sometimes breaks as organizations identify who is 'ready now' and who is 'on track' for larger leadership roles. From this perspective, talent management designs structured approach and a robust mechanism for high potential employees to meet organization’s needs. The paper attempts to provide a roadmap and a structured approach towards building a high performing organization through well-defined career path. Managers want career paths to be defined, so that an adequate number of individuals may be identified and prepared to fill future vacancies. Once career progression patterns are identified, more systematic forecasting of talent requirements is possible. For the development of senior management talent or leadership team, career paths are needed as guidelines for talent management across functional and organizational lines. Career path is one of the important tools for talent management and aligning talent with business strategy. This paper briefly describes the approach for career path and the concept of

Keywords: career path, career path framework, lateral movement, talent management

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Authors: Wesam Jasim, Dongbing Gu

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This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotors path tracking. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR to stabilize the quadrotor and successfully track different paths. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.

Keywords: iLQR controller, optimal control, path tracking, quadrotor UAVs

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Authors: Meetty Tomy, Arxhana G Thosar

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This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

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Authors: Noe Brice Nkoumbou Kaptchouang, Pierre-Guy Vincent, Yann Monerie

Abstract:

The present work addresses the modelling and the simulation of crack initiation and propagation in ductile materials which failed by void nucleation, growth, and coalescence. One of the current research frameworks on crack propagation is the use of cohesive-volumetric approach where the crack growth is modelled as a decohesion of two surfaces in a continuum material. In this framework, the material behavior is characterized by two constitutive relations, the volumetric constitutive law relating stress and strain, and a traction-separation law across a two-dimensional surface embedded in the three-dimensional continuum. Several cohesive models have been proposed for the simulation of crack growth in brittle materials. On the other hand, the application of cohesive models in modelling crack growth in ductile material is still a relatively open field. One idea developed in the literature is to identify the traction separation for ductile material based on the behavior of a continuously-deforming unit cell failing by void growth and coalescence. Following this method, the present study proposed a semi-analytical cohesive model for ductile material based on a micromechanical approach. The strain localization band prior to ductile failure is modelled as a cohesive band, and the Gurson-Tvergaard-Needleman plasticity model (GTN) is used to model the behavior of the cohesive band and derived a corresponding traction separation law. The numerical implementation of the model is realized using the non-smooth contact method (NSCD) where cohesive models are introduced as mixed boundary conditions between each volumetric finite element. The present approach is applied to the simulation of crack growth in nuclear ferritic steel. The model provides an alternative way to simulate crack propagation using the numerical efficiency of cohesive model with a traction separation law directly derived from porous continuous model.

Keywords: ductile failure, cohesive model, GTN model, numerical simulation

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