Search results for: cloud service models

Authors: Tannia Vindel, Carlos Mejia, Damaris Araujo, Carlos Velasquez, Darlin Trejo

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The DWDM (Dense Wavelenght Division Multiplexing) is in constant growth around the world by consumer demand to meet their needs. Since its inception in this operation arises the need for a system which enable us to expand the communication of an entire nation to improve the computing trends of their societies according to their customs and geographical location. The Honduran Company of Telecommunications (HONDUTEL), provides the internet services and data transport technology with a PDH and SDH, which represents in the Republic of Honduras C. A., the option of viability for the consumer in terms of purchase value and its ease of acquisition; but does not have the efficiency in terms of technological advance and represents an obstacle that limits the long-term socio-economic development in comparison with other countries in the region and to be able to establish a competition between telecommunications companies that are engaged in this heading. For that reason we propose to establish a new technological trend implemented in Europe and that is applied in our country that allows us to provide a data transfer in broadband as it is DWDM, in this way we will have a stable service and quality that will allow us to compete in this globalized world, and that must be replaced by one that would provide a better service and which must be in the forefront. Once implemented the DWDM is build upon the existing resources, such as the equipment used, and you will be given life to a new stage providing a business image to the Republic of Honduras C,A, as a nation, to ensure the data transport and broadband internet to a meaningful relationship. Same benefits in the first instance to existing customers and to all the institutions were bidden to these public and private need of such services.

Keywords: demultiplexers, light detectors, multiplexers, optical amplifiers, optical fibers, PDH, SDH

Procedia PDF Downloads 265

Authors: Paivi Hietanen

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At family with children, divorce is a risk for a child to lose the relationship to the parent with whom the child doesn't live. A child has the right to the get care from both parents after the divorce. Even though your ex-spouse isn’t longer your companion, to the child he or she is still unique as a parent and parents must cooperate and support their child in the new family situation. To divorcee, it's necessary to understand the difference between the intimate relationship that ends and parenthood that continues. Cooperative parenting takes a lot of effort and flexibility for the parents to make joint custody work well. It is vital that parents get help to understand the situation from child points of view. When parent is facing divorce, and all the emotions that it brings along, can the child easily be forgotten. To help children, we must help parents to understand, that a relationship can end, parenthood cannot. As professionals, we should help the parents to see the significance and value of both parents to the child and try to support and protect parenthood-relationship between parents. The Federation of Mother and Child Homes and Shelters have developed group models to work with parents during or after divorce. These support groups are led by professionals, but peer support is also used. These support groups have been held over 10 years and there are found from 20 different cities in Finland. Eroneuvo event (divorce advice) service is intended for parents who are considering or have already divorced. The Vanhemman neuvo (parents' council) is a peer support group that helps parents with post-divorce parenting issues. From these groups, parents receive information and peer support for matters related to divorcing and how to support the child and do co-parenting. At the groups and in given information for divorced parents, is used a method called the 'Irreversible triangle'. It's a way to picture the intimate relationship and parenthood after the divorce and what is the difference between these two things. 'Irreversible triangle' is used to help parents and professionals to understand, what happens if a child loses the relationship to the other parent or if parents co-parenting doesn't work well. From the largely collected feedback, group members tell that they feel themselves relieved after taking part of the group. Parents also experience that talking with other parents helps to survive. Group members learn to co-operate with the other parent, and they'll also learn to see the best interest of the child after the divorce. Parents would highly recommend these groups to other parents.

Keywords: child's right, co-parenting, parenthood after the divorce, peer support

Procedia PDF Downloads 167

Authors: Haoyi Sheng

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China's aging tendency is becoming increasingly severe, which leads to the embarrassing situation of "getting old before getting wealthy". The traditional pension model does not comply with the need of today. Relying on "Internet Plus", it can efficiently integrate information and resources and meet the personalized needs of elderly care. It can reduce the operating cost of community elderly care facilities and lay a technical foundation for providing better services for the elderly. The key for providing help for the elderly in the future is to effectively integrate technology, make good use of technology, and improve the efficiency of elderly care services. The effective integration of traditional home care, community care, intelligent elderly care equipment and medical resources to create the "Internet Plus" community intelligent pension service mode has become the future development trend of aging care. The research method of this paper is to collect literature and conduct theoretical research on community pension firstly. Secondly, the combination of suitable aging design and "Internet Plus" is elaborated through research. Finally, this paper states the current level of intelligent technology in old-age care and looks into the future by understanding multiple levels of "Internet Plus". The development of community intelligent pension mode and content under "Internet Plus" has enormous development potential. In addition to the characteristics and functions of ordinary houses, residential design of endowment housing has higher requirements for comfort and personalization, and the people-oriented is the principle of design.

Keywords: ageing tendency, 'Internet Plus', community intelligent elderly care, elderly care service model, technology

Procedia PDF Downloads 138

Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Sourabh Jain, Parul Madan

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Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Xu Jie

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As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decisionmaking problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security). By modeling the multi-job collaborative cryptographic service scheduling problem as a multiobjective optimized job flow scheduling problem, and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing, and effectively solves the problem of complex resource scheduling in cryptographic services.

Keywords: multi-agent reinforcement learning, non-stationary dynamics, multi-agent systems, cooperative and competitive agents

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Authors: Carolina Payares-Asprino

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Dual-phase duplex stainless steel comprised of ferrite and austenite has shown high strength and corrosion resistance in many aggressive environments. Joining duplex alloys is challenging due to several embrittling precipitates and metallurgical changes during the welding process. The welding parameters strongly influence the quality of a weld joint. Therefore, it is necessary to quantify the weld bead’s integral properties as a function of welding parameters, especially when part of the weld bead is removed through a machining process due to aesthetic reasons or to couple the elements in the in-service structure. The present study uses the existing stress-strain model to predict the stress-strain curves for duplex stainless-steel welds under different welding conditions. Having mathematical expressions that predict the shape of the stress-strain curve is advantageous since it reduces the experimental work in obtaining the tensile test. In analysis and design, such stress-strain modeling simplifies the time of operations by being integrated into calculation tools, such as the finite element program codes. The elastic zone and the plastic zone of the curve can be defined by specific parameters, generating expressions that simulate the curve with great precision. There are empirical equations that describe the stress-strain curves. However, they only refer to the stress-strain curve for the stainless steel, but not when the material is under the welding process. It is a significant contribution to the applications of duplex stainless steel welds. For this study, a 3x3 matrix with a low, medium, and high level for each of the welding parameters were applied, giving a total of 27 weld bead plates. Two tensile specimens were manufactured from each welded plate, resulting in 54 tensile specimens for testing. When evaluating the four models used to predict the stress-strain curve in the welded specimens, only one model (Rasmussen) presented a good correlation in predicting the strain stress curve.

Keywords: duplex stainless steels, modeling, stress-stress curve, tensile test, welding

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Authors: Ribut Alam Malau, Durri Andriani, C. B. Supartomo

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Universitas Terbuka (UT) as a higher education institution implements open and distance education is responsible to provide higher education to all Indonesian citizen wherever they live, including those reside in cultural diversity aras. Operate from Jakarta Head Office and 37 regional centers (ROs), UT is accustomed to the challenge. UT-Kupang and UT-Ambon which oversee East Nusa Tenggara and Maluku have successfully provided quality educational services for students. The two ROs have provided educational facilities which could assist the students to cope with their study in spite of the diversity situations. In order to analyze the effectiveness of the facilities provided, questionnaires focusing on tutorial services were sent to 90 students in the two ROs asking them to assess the facilities which best fulfills students’ needs in terms of their culture diversity. The results showed that UT-Kupang and UT-Ambon have successful in providing education for students in their areas as reflected in more than 80% of respondents aware of the facilities concerning tutorial service except for tutorial mechanism where only 34,5% of respondents aware of. However, despite lower rate of awareness in tutorial mechanism, majority of respondent 90.8% of respondents registered in tutorials and 95.4% will register in tutorials next semester. The majority of respondents showed appreciation for the ROs efforts to provide tutorials on weekdays which could accommodate their beliefs. In addition, conducting tutorials in all islands also perceived highly since students did not have to commute between islands. Efforts done by UT-Kupang and UT-Ambon have proven to be appreciated by students.

Keywords: archipelago, cultural diversity, ODL, service quality, Universitas Terbuka

Procedia PDF Downloads 473

Authors: Gregory E. Ofili

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Introduction and Objective: Climate change and a global economy mean farmers must adapt and gain access to affordable and reliable automation technologies. Key barriers include a lack of transportation, electricity, and internet service, coupled with costly enabling technologies and limited local subject matter expertise. Methodology/Approach: Resourcefulness is essential to mechanization on a farm. This runs contrary to the tech industry practice of planned obsolescence and disposal. One solution is plug-and-play hardware that allows farmer to assemble, repair, program, and service their own fleet of industrial machines. To that end, we developed a method of manufacturing low-cost utility robots, transport vehicles, and solar/wind energy harvesting systems, all running on an open-source Robot Operating System (ROS). We demonstrate this technology by fabricating a utility robot and an all-terrain (4X4) utility vehicle. Constructed of aluminum trusses and weighing just 40 pounds, yet capable of transporting 200 pounds of cargo, on sale for less than $2,000. Conclusions & Policy Implications: Electricity, internet, and automation are essential for productivity and competitiveness. With planned obsolescence, the priorities of technology suppliers are not aligned with the farmer’s realities. This patent-pending method of manufacturing low-cost industrial robots and electric vehicles has met its objective. To create low-cost machines, the farmer can assemble, program, and repair with basic hand tools.

Keywords: automation, robotics, utility robot, small-hold farm, robot operating system

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Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

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The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: cloud forensics, data protection Laws, GDPR, IoT forensics, machine Learning

Procedia PDF Downloads 150

Authors: W. Sriwattanapongse, S. Prasitwattanaseree, S. Wongtrangan

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The transportation accidents mortality is a major problem that leads to loss of human lives, and economic. The objective was to identify patterns of statistical modeling for estimating mortality rates due to transportation accidents in Thailand by using data from 2000 to 2009. The data was taken from the death certificate, vital registration database. The number of deaths and mortality rates were computed classifying by gender, age, year and region. There were 114,790 cases of transportation accidents deaths. The highest average age-specific transport accident mortality rate is 3.11 per 100,000 per year in males, Southern region and the lowest average age-specific transport accident mortality rate is 1.79 per 100,000 per year in females, North-East region. Linear, poisson and negative binomial models were chosen for fitting statistical model. Among the models fitted, the best was chosen based on the analysis of deviance and AIC. The negative binomial model was clearly appropriate fitted.

Keywords: transportation accidents, mortality, modeling, analysis of deviance

Procedia PDF Downloads 246

Authors: M. Ezzat, Y. Zaghloul, T. Sorour, A. Hefny, M. Eid

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Ultimate capacity of large diameter bored piles is usually determined from pile loading tests as recommended by several international codes and foundation design standards. However, loading of this type of piles till achieving apparent failure is practically seldom. In this paper, numerical analyses are carried out to simulate load test of a large diameter bored pile performed at the location of Alzey highway bridge project (Germany). Test results of pile load settlement relationship till failure as well as results of the base and shaft resistances are available. Apparent failure was indicated in this test by the significant increase of the induced settlement during the last load increment applied on the pile head. Measurements of this pile load test are used to assess the quality of the numerical models investigated. Three different material soil models are implemented in the analyses: Mohr coulomb (MC), Soft soil (SS), and Modified Mohr coulomb (MMC). Very good agreement is obtained between the field measured settlement and the calculated settlement using the MMC model. Results of analysis showed also that the MMC constitutive model is superior to MC, and SS models in predicting the ultimate base and shaft resistances of the large diameter bored pile. After calibrating the numerical model, behavior of large diameter bored piles under axial loads is discussed and the formation of the plastic zone around the pile is explored. Results obtained showed that the plastic zone below the base of the pile at failure extended laterally to about four times the pile diameter and vertically to about three times the pile diameter.

Keywords: ultimate capacity, large diameter bored piles, plastic zone, failure, pile load test

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Authors: Nadjib Melkemi, Salah Belaidi

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Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

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Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-Destructive Techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: rebound, ultra-sonic pulse, penetration, ANN, NDT, regression

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Authors: Janika Vien K. Valsorable, Filma C. Calalo

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Climate change is one of the most damaging and serious environmental threats worldwide being faced today. While almost everyone highly depends and puts their trust on what technology, innovations, and initiatives from hard-core science can do to cope with the changing climate, there are still people who find hope on indigenous knowledge systems. The study aimed to analyze the traditional farming practices of the Dumagats in Tanay, Rizal and how these relate to their adaptation and mitigation of climate change. The analysis is based on interviews with 17 members of the Dumagat tribe specifically residing in Barangay Cuyambay, San Andres, and Mamuyao, and supported by Key Informant Interview and Focus Group Discussion as well as document reviews. Results of the study showed that the Dumagats adopt indigenous knowledge systems and their high sensitivity and resilience to climate change aid them in their farming system and activities. These traditional farming practices are exemplified from land preparation to planting, fertilizer application, weed and pest management, harvesting and post-harvest activities. Owing to their dependence upon, and close relationship with the environment and its resources, the Dumagats have learned to interpret and react to the impacts of climate change in creative ways, drawing on their traditional knowledge to cope with the impending changes. With the increasing trend at all levels of government to service the needs of rural communities, there is the need for the extension to contextualize advisory service delivery for indigenous communities.

Keywords: climate change, Dumagat tribe, indigenous knowledge systems, traditional farming practices

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Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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Authors: Roberta Gentry

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A mixed methods study that examined candidate’s perceptions of the use of computerized simulation as an effective tool to learn classroom management will be presented. The development, implementation, and assessment of the simulation and candidate data on the feasibility of the approach in comparison to other methods will be presented.

Keywords: behavior management, simulations, teacher preparation, teacher education

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Authors: Molly Parker

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Unintended pregnancy rates in Australia are amongst the highest in the developed world. Women with Substance Use Disorder often have riskier sexual behavior with nil contraceptive use and face disproportionately higher unintended pregnancies and Sexually Transmitted Infections, alongside Substance Use in Pregnancy (SUP) climbing at an alarming rate. In an inner-city Drug and Alcohol (D&A) service, significant barriers to sexual and reproductive health services have been identified, aligning with research. Rapid pathways were created for women seeking D&A treatment to be referred to Sexual and Reproductive Health services for the administration of Long-acting reversible contraception (LARC) and sexual health screening. For clients attending a D&A service, this is an opportunistic time to offer sexual and reproductive health services. Collaboration and multidisciplinary team input between D&A and sexual health and reproductive services are paramount, with rapid referral pathways being identified as the main strategy to improve access to sexual and reproductive health support for this population. With this evidence, a rapid referral pathway was created for women using the D&A service to access LARC, particularly in view of fertility often returning once stable on D&A treatment. A closed-ended survey was used for D&A staff to identify gaps in reproductive health knowledge and views of referral accessibility. Results demonstrated a lack of knowledge of contraception and appropriate referral processes. A closed-ended survey for clients was created to establish the need and access to services and to quantify data. A follow-up data collection will be reviewed to access uptake and satisfaction of the intervention from clients. Sexual health screening access was also identified as a deficit, particularly concerning due to the higher rates of STIs in this cohort. A rapid referral pathway will be undergoing implementation, reducing risks of untreated STIS both pre and post-conception. Similarly, pre and post-intervention structured surveys will be used to identify client satisfaction from the pathway. Although currently in progress, the research and pathway aim to be completed by December 2023. This research and implementation of sexual and reproductive health pathways from the D&A service have significant health and well-being benefits to clients and the wider community, including possible fetal/infancy outcomes. Women now have rapid access to sexual and reproductive health services, with the aim of reducing unplanned pregnancies, poor outcomes associated with SUP, client/staff trauma from termination of pregnancy, and client/staff trauma following the assumption of care of the child due to substance use, the financial cost for out of home care as required, the poor outcomes of untreated STIs to the fetus in pregnancy and the spread of STIs in the wider community. As evidence suggests, the implementation of a streamlined referral process is required between D&A and sexual and reproductive health services and has positive feedback from both clinicians and clients in improving care.

Keywords: substance use in pregnancy, drug and alcohol, substance use disorder, sexual health, reproductive health, contraception, long-acting reversible contraception, neonatal abstinence syndrome, FASD, sexually transmitted infections, sexually transmitted infections pregnancy

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Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

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Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

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Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

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Authors: T. Heikkinen, J. Oksman, T. Bragge, A. Nurmi, O. Kontkanen, T. Ahtoniemi

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Motor impairment is an inherent phenotypic feature of several chronic neurodegenerative diseases, and pharmacological therapies aimed to counterbalance the motor disability have a great market potential. Animal models of chronic neurodegenerative diseases display a number deteriorating motor phenotype during the disease progression. There is a wide array of behavioral tools to evaluate motor functions in rodents. However, currently existing methods to study motor functions in rodents are often limited to evaluate gross motor functions only at advanced stages of the disease phenotype. The most commonly applied traditional motor assays used in CNS rodent models, lack the sensitivity to capture fine motor impairments or improvements. Fine motor skill characterization in rodents provides a more sensitive tool to capture more subtle motor dysfunctions and therapeutic effects. Importantly, similar approach, kinematic movement analysis, is also used in clinic, and applied both in diagnosis and determination of therapeutic response to pharmacological interventions. The aim of this study was to apply kinematic gait analysis, a novel and automated high precision movement analysis system, to characterize phenotypic deficits in three different chronic neurodegenerative animal models, a transgenic mouse model (SOD1 G93A) for amyotrophic lateral sclerosis (ALS), and R6/2 and Q175KI mouse models for Huntington’s disease (HD). The readouts from walking behavior included gait properties with kinematic data, and body movement trajectories including analysis of various points of interest such as movement and position of landmarks in the torso, tail and joints. Mice (transgenic and wild-type) from each model were analyzed for the fine motor kinematic properties at young ages, prior to the age when gross motor deficits are clearly pronounced. Fine motor kinematic Evaluation was continued in the same animals until clear motor dysfunction with conventional motor assays was evident. Time course analysis revealed clear fine motor skill impairments in each transgenic model earlier than what is seen with conventional gross motor tests. Motor changes were quantitatively analyzed for up to ~80 parameters, and the largest data sets of HD models were further processed with principal component analysis (PCA) to transform the pool of individual parameters into a smaller and focused set of mutually uncorrelated gait parameters showing strong genotype difference. Kinematic fine motor analysis of transgenic animal models described in this presentation show that this method isa sensitive, objective and fully automated tool that allows earlier and more sensitive detection of progressive neuromuscular and CNS disease phenotypes. As a result of the analysis a comprehensive set of fine motor parameters for each model is created, and these parameters provide better understanding of the disease progression and enhanced sensitivity of this assay for therapeutic testing compared to classical motor behavior tests. In SOD1 G93A, R6/2, and Q175KI mice, the alterations in gait were evident already several weeks earlier than with traditional gross motor assays. Kinematic testing can be applied to a wider set of motor readouts beyond gait in order to study whole body movement patterns such as with relation to joints and various body parts longitudinally, providing a sophisticated and translatable method for disseminating motor components in rodent disease models and evaluating therapeutic interventions.

Keywords: Gait analysis, kinematic, motor impairment, inherent feature

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Authors: P. S. Hsi, Y. F. Wang, Y. F. Ho, P. C. Hung

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The aim of the present study was to explore the dermal exposure assessment model of chemicals that have been developed abroad and to evaluate the feasibility of chemical dermal exposure assessment model for manufacturing industry in Taiwan. We conducted and analyzed six semi-quantitative risk management tools, including UK - Control of substances hazardous to health ( COSHH ) Europe – Risk assessment of occupational dermal exposure ( RISKOFDERM ), Netherlands - Dose related effect assessment model ( DREAM ), Netherlands – Stoffenmanager ( STOFFEN ), Nicaragua-Dermal exposure ranking method ( DERM ) and USA / Canada - Public Health Engineering Department ( PHED ). Five types of manufacturing industry were selected to evaluate. The Monte Carlo simulation was used to analyze the sensitivity of each factor, and the correlation between the assessment results of each semi-quantitative model and the exposure factors used in the model was analyzed to understand the important evaluation indicators of the dermal exposure assessment model. To assess the effectiveness of the semi-quantitative assessment models, this study also conduct quantitative dermal exposure results using prediction model and verify the correlation via Pearson's test. Results show that COSHH was unable to determine the strength of its decision factor because the results evaluated at all industries belong to the same risk level. In the DERM model, it can be found that the transmission process, the exposed area, and the clothing protection factor are all positively correlated. In the STOFFEN model, the fugitive, operation, near-field concentrations, the far-field concentration, and the operating time and frequency have a positive correlation. There is a positive correlation between skin exposure, work relative time, and working environment in the DREAM model. In the RISKOFDERM model, the actual exposure situation and exposure time have a positive correlation. We also found high correlation with the DERM and RISKOFDERM models, with coefficient coefficients of 0.92 and 0.93 (p<0.05), respectively. The STOFFEN and DREAM models have poor correlation, the coefficients are 0.24 and 0.29 (p>0.05), respectively. According to the results, both the DERM and RISKOFDERM models are suitable for performance in these selected manufacturing industries. However, considering the small sample size evaluated in this study, more categories of industries should be evaluated to reduce its uncertainty and enhance its applicability in the future.

Keywords: dermal exposure, risk management, quantitative estimation, feasibility evaluation

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Authors: Ahmed Al-Adaileh, Souheil Khaddaj

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Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.

Keywords: smart energy management systems, internet of things, wireless mesh networks, microservices, cloud computing, big data

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Authors: Joy Olayemi Gbala, Fatai Olatokunbo, Philip Cloud

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Catastrophic dictatorship has been discovered to be the major leadership challenge that orchestrates stagnated and contrasted economy with dysfunctional democracy in Africa through willful misappropriation of resources and egregious subversion of the rule of law. Almost invariably, most African leaders inexplicably often become power drunk and addicted which usually leads to abuse of state power, abdication of constitutional duties, unjustly withdrawal of business license of operation, human right violation, election malpractices, financial corruption, disruptions of policies of democratic government transition, annulment of free and fair election, and disruptions of legal electoral procedures and unachievable dividends of democracy and many more. Owing to this, most African nations have gone and still go through political unrest and insurgencies leading to loss of lives and property, violent protests, detention of detractors and political activists and massive human displacement. This research work is concerned with, and investigates the causes, menace, consequences and impacts of subverting the rule of law in Africa on the economy and the development of the continent with a suggested practical solution to the plights.

Keywords: corruption, law, leadership, violation

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Authors: Maria Joseph Israel, Ahmed Amer

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Our work aims to broaden the application of provenance technology beyond its traditional domains of scientific workflow management and database systems by offering a general provenance framework to capture richer and extensible metadata in unstructured textual data sources such as literary texts, commentaries, translations, and digital humanities. Specifically, we demonstrate the feasibility of capturing and representing expressive provenance metadata, including more of the context for citing scholarly works (e.g., the authors’ explicit or inferred intentions at the time of developing his/her research content for publication), while also supporting subsequent augmentation with similar additional metadata (by third parties, be they human or automated). To better capture the nature and types of possible citations, in our proposed provenance scheme metaScribe, we extend standard provenance conceptual models to form our proposed provCite ontology. This provides a conceptual framework which can accurately capture and describe more of the functional and rhetorical properties of a citation than can be achieved with any current models.

Keywords: knowledge representation, provenance architecture, ontology, metadata, bibliographic citation, semantic web annotation

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Authors: Bello Abdullahi, Kabir Bala, Yahaya M. Ibrahim, Ahmed D. Ibrahim

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Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent, and more prone to manipulations and errors. However, the advent of the Internet and its associated technologies has led to the development of numerous e-Tendering systems that addressed many of the problems associated with the manual paper-based tendering system. Currently, in Nigeria, the public tendering processes are largely conducted based on manual paper-based system that is bedevilled by a number of problems such as inordinate delays, inefficiencies, manipulation of the tender evaluation process, corruption, lack of transparency and competition, among other problems. These problems can be addressed through the adoption of existing web-based e-Tendering systems which are known to address most of these problems. However, these existing e-Tendering systems that have been developed are not based on the Nigerian legal procurement processes and as such their suitability for local application is very limited. This paper is part of a larger study that attempt to address this problem through the development of an e-Tendering system that is based on the requirements of the Nigerian public procuring entities. In this paper, the identified tendering processes commonly used by Nigerian public procuring entities in the selection of construction sources are presented. A multi-methods research approach was used to identify those tendering processes. Specifically, 19 existing business use cases used by Nigerian public procuring entities were identified and 61 system use cases were prescribed based on the identified business use cases. The use cases were used as the basis for the development of domain and software conceptual models. The models were successfully used to guide the development of an e-Tendering system called NPS-eTender. Ripple and Unified Process were adopted as the software development methodologies.

Keywords: e-tendering, e-procurement, requirement model, conceptual model, public sector tendering, public procurement

Procedia PDF Downloads 200