Search results for: building information modeling

Authors: Hasen Keder Edris, Ryuji Matsunaga, Toshi Yamanaka

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The issue of climate change and its impact is a major contemporary global concern. Ethiopia is one of the countries experiencing adverse climate change impact including frequent extreme weather events that are exacerbating drought and water scarcity. Due to this reason, the government of Ethiopia develops a strategic document which focuses on the climate resilience green economy. One of the major components of the strategic framework is designed to improve community adaptation capacity and mitigation of drought. For effective implementation of the strategy, identification of regions relative vulnerability to drought is vital. There is a growing tendency of applying Geographic Information System (GIS) and Remote Sensing technologies for collecting information on duration and severity of drought by direct measure of the topography as well as an indirect measure of land cover. This study aims to show an application of remote sensing technology and GIS for developing drought vulnerability index by taking lowland of Ethiopia as a case study. In addition, it assesses integrated Information Communication Technology (ICT) potential of Ethiopia lowland and proposes integrated solution. Satellite data is used to detect the beginning of the drought. The severity of drought risk prone areas of livestock keeping pastoral is analyzed through normalized difference vegetation index (NDVI) and ten years rainfall data. The change from the existing and average SPOT NDVI and vegetation condition index is used to identify the onset of drought and potential risks. Secondary data is used to analyze geographical coverage of mobile and internet usage in the region. For decades, the government of Ethiopia introduced some technologies and approach to overcoming climate change related problems. However, lack of access to information and inadequate technical support for the pastoral area remains a major challenge. In conventional business as usual approach, the lowland pastorals continue facing a number of challenges. The result indicated that 80% of the region face frequent drought occurrence and out of this 60% of pastoral area faces high drought risk. On the other hand, the target area mobile phone and internet coverage is rapidly growing. One of identified ICT solution enabler technology is telecom center which covers 98% of the region. It was possible to identify the frequently affected area and potential drought risk using the NDVI remote-sensing data analyses. We also found that ICT can play an important role in mitigating climate change challenge. Hence, there is a need to strengthen implementation efforts of climate change adaptation through integrated Remote Sensing and web based information dissemination and mobile alert of extreme events.

Keywords: climate changes, ICT, pastoral, remote sensing

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Authors: M. Priscila Ramos, Omar O. Chisari, Juan Pablo Vila Martínez

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Current literature about trade liberalization of environmental goods and services (EGS) raises doubts about the extent of the triple win-win situation for trade, development and the environment. However, much of this literature does not consider the possibility that this agreement carries technological transmissions, either through trade or foreign direct investment. This paper presents a computable general equilibrium model calibrated for Argentina, where there are alternative technologies (one dirty and one clean according to carbon emissions) to produce the same goods. In this context, the trade liberalization of EGS allows to increase GDP, trade, reduce unemployment and improve the households welfare. However, the capital mobility appears as the key assumption to jointly reach the environmental target, when the positive scale effect generated by the increase in trade is offset by the change in the composition of production (composition and technical effects by the use of the clean alternative technology) and of consumption (composition effect by substitution of relatively lesspolluting imported goods).

Keywords: CGE modeling, CO2 emissions, composition effect, scale effect, technique effect, trade liberalization of EGS

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Authors: Julio Kauss, Miguel Cadillo, David Mauricio

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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: e-commerce, retail, SMEs, reference model

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Authors: Merve Akca

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Retrieval-induced forgetting (RIF) refers to the phenomenon that selective retrieval of some information impairs memory for related, but not previously retrieved information. Despite age differences in retrieval-induced forgetting regarding retrospective memory being documented, this research aimed to highlight age differences in RIF of the prospective memory tasks for the first time. By using retrieval-practice paradigm, this study comparatively examined RIF effects in retrospective memory and event-based prospective memory in young and old adults. In this experimental study, a mixed factorial design with age group (Young, Old) as a between-subject variable, and memory type (Prospective, Retrospective) and item type (Practiced, Non-practiced) as within-subject variables was employed. Retrieval-induced forgetting was observed in the retrospective but not in the prospective memory task. Therefore, the results indicated that selective retrieval of past events led to suppression of other related past events in both age groups but not the suppression of memory for future intentions.

Keywords: prospective memory, retrieval-induced forgetting, retrieval inhibition, retrospective memory

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Authors: Wenbo Du, Xiaomei Ma

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With the empowerment of Cognitive Diagnostic Assessment (CDA), various domains of language testing and assessment have been investigated to dig out more diagnostic information. What is noticeable is that most of the extant empirical CDA-based research puts much emphasis on individual-level diagnostic purpose with very few concerned about learners’ group-level performance. Even though the personalized diagnostic feedback is the unique feature that differentiates CDA from other assessment tools, group-level diagnostic information cannot be overlooked in that it might be more practical in classroom setting. Additionally, the group-level diagnostic information obtained via current CDA always results in a “flat pattern”, that is, the mastery/non-mastery of all tested skills accounts for the two highest proportion. In that case, the outcome does not bring too much benefits than the original total score. To address these issues, the present study attempts to apply cluster analysis for group classification and quantile regression analysis to pinpoint learners’ performance at different proficiency levels (beginner, intermediate and advanced) thus to enhance the interpretation of the CDA results extracted from a group of EFL learners’ reading performance on a diagnostic reading test designed by PELDiaG research team from a key university in China. The results show that EM method in cluster analysis yield more appropriate classification results than that of CDA, and quantile regression analysis does picture more insightful characteristics of learners with different reading proficiencies. The findings are helpful and practical for instructors to refine EFL reading curriculum and instructional plan tailored based on the group classification results and quantile regression analysis. Meanwhile, these innovative statistical methods could also make up the deficiencies of CDA and push forward the development of language testing and assessment in the future.

Keywords: cognitive diagnostic assessment, diagnostic feedback, EFL reading, quantile regression

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: Bill D. Geis

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Suicide wrongful death forensic cases are the fastest rising tort in mental health law. It is estimated that suicide-related cases have accounted for 15% of U.S. malpractice claims since 2006. Most suicide-related personal injury claims fall into the legal category of “wrongful death.” Though mental health experts may be called on to address a range of forensic questions in wrongful death cases, the central consultation that most experts provide is about the negligence element—specifically, the issue of whether the clinician met the clinical standard of care in assessing, treating, and managing the deceased person’s mental health care. Standards of care, varying from U.S. state to state, are broad and address what a reasonable clinician might do in a similar circumstance. This fact leaves the issue of the suicide standard of care, in each case, up to forensic experts to put forth a reasoned estimate of what the standard of care should have been in the specific case under litigation. Because the general state guidelines for standard of care are broad, forensic experts are readily retained to provide scientific and clinical opinions about whether or not a clinician met the standard of care in their suicide assessment, treatment, and management of the case. In the past and in much of current practice, the assessment of suicide has centered on the elicitation of verbalized suicide ideation. Research in recent years, however, has indicated that the majority of persons who end their lives do not say they are suicidal at their last medical or psychiatric contact. Near-term risk assessment—that goes beyond verbalized suicide ideation—is needed. Our previous research employed structural equation modeling to predict lethal suicide risk--eight negative thought patterns (feeling like a burden on others, hopelessness, self-hatred, etc.) mediated by nine transdiagnostic clinical factors (mental torment, insomnia, substance abuse, PTSD intrusions, etc.) were combined to predict acute lethal suicide risk. This structural equation model, the Lethal Suicide Risk Pattern (LSRP), Acute model, had excellent goodness-of-fit [χ2(df) = 94.25(47)***, CFI = .98, RMSEA = .05, .90CI = .03-.06, p(RMSEA = .05) = .63. AIC = 340.25, ***p < .001.]. A further SEQ analysis was completed for this paper, adding a measure of Acute Suicide Ideation to the previous SEQ. Acceptable prediction model fit was no longer achieved [χ2(df) = 3.571, CFI > .953, RMSEA = .075, .90% CI = .065-.085, AIC = 529.550].This finding suggests that, in this additional study, immediate verbalized suicide ideation information was unhelpful in the assessment of lethal risk. The LSRP and other dynamic, near-term risk models (such as the Acute Suicide Affective Disorder Model and the Suicide Crisis Syndrome Model)—going beyond elicited suicide ideation—need to be incorporated into current clinical suicide assessment training. Without this training, the standard of care for suicide assessment is out of sync with current research—an emerging dilemma for the forensic evaluation of suicide wrongful death cases.

Keywords: forensic evaluation, standard of care, suicide, suicide assessment, wrongful death

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Authors: Hsiaoping Wu

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With the wide use of Internet, learners are exposed to the wider world. This exposure permits learners to discover new information and combine a variety of media in order to reach in-depth and broader understanding of their literacy and the world. Many paper-based teaching, learning and assessment modalities can be transferred to a digital platform. This study examines the use of e-portfolios for ESL (English as a second language) pre-service teacher. The data were collected by reviewing 100 E-portfolio from 2013 to 2015 in order to synthesize meaningful information about e-portfolios for ESL pre-service teachers. Participants were generalists, bilingual and ESL pre-service teachers. The studies were coded into two main categories: learning gains, including assessment, and technical skills. The findings showed that using e-portfolios enhanced and developed ESL pre-service teachers’ teaching and assessment skills. Also, the E-portfolio also developed the pre-service teachers’ technical stills to prepare a comprehensible portfolio to present who they are. Finally, the study and presentation suggested e-portfolios for ecological issues and educational purposes.

Keywords: assessment, e-portfolio, pre-service teacher, reflection

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Authors: Fatih Iscan, Ceren Yagci

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Rapid population growth, urbanization and industrialization are known as the most important factors of environment problems. Elimination and management of solid wastes are also within the most important environment problems. One of the main problems in solid waste management is the selection of the best site for elimination of solid wastes. Lately, Geographical Information System (GIS) has been used for easing selection of landfill area. GIS has the ability of imitating necessary economical, environmental and political limitations. They play an important role for the site selection of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of environmental, social and cultural factors and maximum effect for engineering/economical factors for site selection of landfill areas and using GIS for an decision support mechanism in solid waste landfill areas site selection will be presented in Aksaray/TURKEY city, Güzelyurt district practice.

Keywords: GIS, landfill, solid waste, spatial analysis

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we briefly introduce the concept of Poisson attacks in the case of defense/attack strategies where attacks are assumed to be continuous. We suggest a game model in which the attacker will combine both criteria of a sufficient confidence level of a successful attack and a reasonably small size of the estimation error in order to launch an attack. Here, estimation error arises from assessing the system failure upon attack using aggregate data at the system level. The corresponding error is referred to as aggregation error. On the other hand, the defender will attempt to deter attack by making one or both criteria inapplicable. The defender will build his/her strategy by both strengthening the targeted system and increasing the size of error. We will formulate the defender problem based on appropriate optimization models. The attacker will opt for a Bayesian updating in assessing the impact on the improvement made by the defender. Then, the attacker will evaluate the feasibility of the attack before making the decision of whether or not to launch it. We will provide illustrations to better explain the process.

Keywords: attacker, defender, game theory, information

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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Authors: Rama Seth, Luise Noring, Pratim Majumdar

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Based on an extensive literature review, this paper presents distinct approaches to value, quantify and trade ecosystem services, with particular emphasis on services provided by mangroves and wetlands. Building on diverse monetary and market-based systems for the improved allocation of natural resources, such trading and exchange-based methods can help tackle the degradation of ecosystem services in a more targeted and structured manner than achievable with stand-alone policy and administrative regulations. Using various threads of literature, the paper proposes a platform that serves as the skeletal foundation for developing an efficient global market for ecosystem services trading. The paper bridges a significant research and practice gap by recommending how to establish an equilibrium in the biosphere via trading mechanisms while also discovering other research gaps and future research potential in the domain of ecosystem valuation.

Keywords: environment, economics, mangroves, wetlands, markets, ESG, global capital, climate investments, valuation, ecosystem services

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Authors: Oh Hyeon Jeon, WooYoung Jung

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In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.

Keywords: weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo simulation, permeability coefficient

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: John Tolentino, Yong Seok Park

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There are currently many people living with limb loss in the USA. The main causes for amputation can range from vascular disease, to trauma, or cancer. This number is expected increase over the next decade. Many patients have a single prosthetic for the first year but end up getting a second one to accommodate their changing physique. Afterwards, the prosthesis gets replaced every three to five years depending on how often it is used. This could cost the patient up to $500,000 throughout their lifetime. Complications do not end there, however. Due to the absence of nerves, it becomes more difficult to traverse terrain with a prosthetic. Moving on an incline or decline becomes difficult, thus curbs and stairs can be a challenge. Certain physical activities, such as cycling, could be even more strenuous. It will need to be relearned to accommodate for the change in weight, center of gravity, and transfer of energy from the leg to the pedal. The purpose of this research project is to develop a new, alternate below-knee cycling prosthetic using Dieter & Schmidt’s design process approach. It will be subjected to fatigue analysis under dynamic loading to observe the limitations as well as the strengths and weaknesses of the prosthetic. Benchmark comparisons will be made between existing prosthetics and the proposed one, examining the benefits and disadvantages. The resulting prosthetic will be 3D printed using acrylonitrile butadiene styrene (ABS) or polycarbonate (PC) plastic.

Keywords: 3D Printing, Cycling, Prosthetic design, Synthetic design.

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Authors: Ombir Singh

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In spite of the religious and cultural pre-dominance of the river Ganga in the Indian ethos, fragmentation and degradation of the river continued down the ages. Recognizing the national concern on environmental degradation of the river and its basin, Ministry of Water Resources, River Development & Ganga Rejuvenation (MoWR,RD&GR), Government of India has initiated a number of pilot schemes for the rejuvenation of river Ganga under the ‘Namami Gange’ Programme. Considering the diversity, complexity, and intricacies of forest ecosystems and pivotal multiple functions performed by them and their inter-connectedness with highly dynamic river ecosystems, forestry interventions all along the river Ganga from its origin at Gaumukh, Uttarakhand to its mouth at Ganga Sagar, West Bengal has been planned by the ministry. For that Forest Research Institute (FRI) in collaboration with National Mission for Clean Ganga (NMCG) has prepared a Detailed Project Report (DPR) on Forestry Interventions for Ganga. The Institute has adopted an extensive consultative process at the national and state levels involving various stakeholders relevant in the context of river Ganga and employed a science-based methodology including use of remote sensing and GIS technologies for geo-spatial analysis, modeling and prioritization of sites for proposed forestation and conservation interventions. Four sets of field data formats were designed to obtain the field based information for forestry interventions, mainly plantations and conservation measures along the river course. In response, five stakeholder State Forest Departments had submitted more than 8,000 data sheets to the Institute. In order to analyze a voluminous field data received from five participating states, the Institute also developed a software to collate, analyze and generation of reports on proposed sites in Ganga basin. FRI has developed potential plantation and treatment models for the proposed forestry and other conservation measures in major three types of landscape components visualized in the Ganga riverscape. These are: (i) Natural, (ii) Agriculture, and (iii) Urban Landscapes. Suggested plantation models broadly varied for the Uttarakhand Himalayas and the Ganga Plains in five participating states. Besides extensive plantations in three type of landscapes within the riverscape, various conservation measures such as soil and water conservation, riparian wildlife management, wetland management, bioremediation and bio-filtration and supporting activities such as policy and law intervention, concurrent research, monitoring and evaluation, and mass awareness campaigns have been envisioned in the DPR. The DPR also incorporates the details of the implementation mechanism, budget provisioned for different components of the project besides allocation of budget state-wise to five implementing agencies, national partner organizations and the Nodal Ministry.

Keywords: conservation, Ganga, river, water, forestry interventions

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Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Kevin Tinkham, Ella Quigley

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Structural integrity for cladding products is a key performance parameter, especially concerning fire performance. Cladding products such as PIR-based sandwich panels are tested rigorously, in line with industrial standards. Physical fire tests are necessary to ensure the customer's safety but can give little information about critical behaviours that can help develop new materials. Numerical modelling is a tool that can help investigate a fire's behaviour further by replicating the fire test. However, fire is an interdisciplinary problem as it is a chemical reaction that behaves fluidly and impacts structural integrity. An analysis using Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is needed to capture all aspects of a fire performance test. One method is a two-way coupling analysis that imports the updated changes in thermal data, due to the fire's behaviour, to the FEA solver in a series of iterations. In light of our recent work with Tata Steel U.K using a two-way coupling methodology to determine the fire performance, it has been shown that a program called FDS-2-Abaqus can make predictions of a BS 476 -22 furnace test with a degree of accuracy. The test demonstrated the fire performance of Tata Steel U.K Trisomet product, a Polyisocyanurate (PIR) based sandwich panel used for cladding. Previous works demonstrated the limitations of the current version of the program, the main limitation being the computational cost of modelling three Trisomet panels, totalling an area of 9 . The computational cost increases substantially, with the intention to scale up to an LPS 1181-1 test, which includes a total panel surface area of 200 .The FDS-2-Abaqus program is developed further within this paper to overcome this obstacle and better accommodate Tata Steel U.K PIR sandwich panels. The new developments aim to reduce the computational cost and error margin compared to experimental data. One avenue explored is a multi-scale approach in the form of Reduced Order Modeling (ROM). The approach allows the user to include refined details of the sandwich panels, such as the overlapping joints, without a computationally costly mesh size.Comparative studies will be made between the new implementations and the previous study completed using the original FDS-2-ABAQUS program. Validation of the study will come from physical experiments in line with governing body standards such as BS 476 -22 and LPS 1181-1. The physical experimental data includes the panels' gas and surface temperatures and mechanical deformation. Conclusions are drawn, noting the new implementations' impact factors and discussing the reasonability for scaling up further to a whole warehouse.

Keywords: fire testing, numerical coupling, sandwich panels, thermo fluids

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Authors: Wassim Katerji, Mercedes Farjas, Carmen Morillo

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Terrain-Based Analysis results in derived products from an input DEM and these products are needed to perform various analyses. To efficiently use these products in decision-making, their accuracies must be estimated systematically. This paper proposes a procedure to assess the accuracy of these derived products, by calculating the accuracy of the slope dataset and its significance, taking as an input the accuracy of the DEM. Based on the output of previously published research on modeling the relative accuracy of a DEM, specifically ASTER and SRTM DEMs with Lebanon coverage as the area of study, analysis have showed that ASTER has a low significance in the majority of the area where only 2% of the modeled terrain has 50% or more significance. On the other hand, SRTM showed a better significance, where 37% of the modeled terrain has 50% or more significance. Statistical analysis deduced that the accuracy of the slope dataset, calculated on a cell-by-cell basis, is highly correlated to the accuracy of the input DEM. However, this correlation becomes lower between the slope accuracy and the slope significance, whereas it becomes much higher between the modeled slope and the slope significance.

Keywords: terrain-based analysis, slope, accuracy assessment, Digital Elevation Model (DEM)

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Kefaifi Aissa, Sahraoui Tahar, Kheloufi Abdelkrim, Anas Sabiha, Hannane Farouk

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The aim of this study is to show how the Design of Experiments Method (DOE) can be put into use as a practical approach for silica sand etching behavior modeling during its primary step of leaching. In the present work, we have studied etching effect on particle size during a primary step of leaching process on Algerian silica sand with florid acid (HF) at 20% and 30 % during 4 and 8 hours. Therefore, a new purity of the sand is noted depending on the time of leaching. This study was expanded by a numerical approach using a method of experiment design, which shows the influence of each parameter and the interaction between them in the process and approved the obtained experimental results. This model is a predictive approach using hide software. Based on the measured parameters experimentally in the interior of the model, the use of DOE method can make it possible to predict the outside parameters of the model in question and can give us the optimize response without making the experimental measurement.

Keywords: acid leaching, design of experiments method(DOE), purity silica, silica etching

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Authors: M. Münch, R. Brandt

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Martensitic steels with an ultimate tensile strength beyond 2000 MPa are applied in the powertrain of vehicles due to their excellent fatigue strength and high creep resistance. However, the creep controlling mechanism in martensitic steels at ambient temperatures up to 423 K is not evident. The purpose of this study is to review the low temperature creep (LTC) behavior of martensitic steels at temperatures from 363 K to 523 K. Thus, the validity of a logarithmic creep law is reviewed and the stress and temperature dependence of the creep parameters α and β are revealed. Furthermore, creep tests are carried out, which include stepped changes in temperature or stress, respectively. On one hand, the change of the creep rate due to a temperature step provides information on the magnitude of the activation energy of the LTC controlling mechanism and on the other hand, the stress step approach provides information on the magnitude of the activation volume. The magnitude, the temperature dependency, and the stress dependency of both material specific activation parameters may deliver a significant contribution to the disclosure of the nature of the LTC rate controlling mechanism.

Keywords: activation parameters, creep mechanisms, high strength steels, low temperature creep

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Authors: Hotlan Siagian, Han Tae Hee

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This study aims to examine the effect of supplier trust and top management involvement on the supply chain risk management through buyer-supplier relationship. The population of the research is 44 Korean companies domiciled in East and Central Java of Indonesia. The respondent consists of a top management level from each company. Data collection used a questionnaire designed with five-item Likert scale. Collected data were analyzed using structural equation modeling (SEM) technique with SmartPLS software version 3.0 to examine the hypotheses. The result revealed that supplier trust has an effect on supply chain risk management, top management involvement affects supply chain risk management, supplier trust influences buyer-supplier relationship, top management involvement affects the buyer-supplier relationship, and buyer-supplier relationship affects supply chain risk management. The last finding is that buyer-supplier relationship empirically mediates the effect of supplier trust and top management involvement.

Keywords: buyer supplier relationship, supplier trust, supply chain risk management, top management involvement

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Authors: Alicia Kamischke, Souhail Elhouar, Yasser Khodair

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The American Institute of Steel Construction (AISC) Specification (360-10) provides equations for calculating the capacity of a W-shaped steel member to resist concentrated forces applied to its flange. In the case of flange local bending, the capacity equations were primarily formulated for an interior point along the member, which is defined to be at a distance larger than ten flange thicknesses away from the member’s end. When a concentrated load is applied within ten flange thicknesses from the member’s end, AISC requires a fifty percent reduction to be applied to the flange bending capacity. This reduction, however, is not supported by any research. In this study, finite element modeling is used to investigate the actual reduction in capacity near the end of such a steel member. The results indicate that the AISC equation for flange local bending is quite conservative for forces applied at less than ten flange thicknesses from the member’s end and a new equation is suggested for the evaluation of available flange local bending capacity within that distance.

Keywords: flange local bending, concentrated forces, column, flange capacity

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Qusay Alghazali, Tibor Cinkler, Abdulhalim Fayad

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In modern optical networks, the flex grid spectrum usage is most widespread, where higher bit rate streams get larger spectrum slices while lower bit rate traffic streams get smaller spectrum slices. To our practice, under the ITU-T recommendation, G.694.1, spectrum slices of 50, 75, and 100 GHz are being used with central frequency at 193.1 THz. However, when these spectrum slices are not sufficient, multiple spectrum slices can use either one next to another or anywhere in the optical wavelength. In this paper, we propose the analysis of the wavelength assignment problem. We compare different algorithms for this spectrum assignment with and without protection. As a reference for comparisons, we concluded that the Integer Linear Programming (ILP) provides the global optimum for all cases. The most scalable algorithm is the greedy one, which yields results in subsequent ranges even for more significant network instances. The algorithms’ benchmark implemented using the LEMON C++ optimization library and simulation runs based on a minimum number of spectrum slices assigned to lightpaths and their execution time.

Keywords: spectrum assignment, integer linear programming, greedy algorithm, international telecommunication union, library for efficient modeling and optimization in networks

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Samuel I. Becher, Tal Z. Zarsky

Abstract:

The digital world becomes part of our DNA now. The way e-commerce, human behavior, and law interact and affect one another is rapidly and significantly changing. Among others things, the internet equips consumers with a variety of platforms to share information in a volume we could not imagine before. As part of this development, online information flows allow consumers to learn about businesses and their contracts in an efficient and quick manner. Consumers can become informed by the impressions that other, experienced consumers share and spread. In other words, consumers may familiarize themselves with the contents of contracts through the experiences that other consumers had. Online and offline, the relationship between consumers and businesses are most frequently governed by consumer standard form contracts. For decades, such contracts are assumed to be one-sided and biased against consumers. Consumer Law seeks to alleviate this bias and empower consumers. Legislatures, consumer organizations, scholars, and judges are constantly looking for clever ways to protect consumers from unscrupulous firms and unfair behaviors. While consumers-businesses relationships are theoretically administered by standardized contracts, firms do not always follow these contracts in practice. At times, there is a significant disparity between what the written contract stipulates and what consumers experience de facto. That is, there is a crucial gap (“the Gap”) between how firms draft their contracts on the one hand, and how firms actually treat consumers on the other. Interestingly, the Gap is frequently manifested by deviation from the written contract in favor of consumers. In other words, firms often exercise lenient approach in spite of the stringent written contracts they draft. This essay examines whether, counter-intuitively, policy makers should add firms’ leniency to the growing list of firms suspicious behaviors. At first glance, firms should be allowed, if not encouraged, to exercise leniency. Many legal regimes are looking for ways to cope with unfair contract terms in consumer contracts. Naturally, therefore, consumer law should enable, if not encourage, firms’ lenient practices. Firms’ willingness to deviate from their strict contracts in order to benefit consumers seems like a sensible approach. Apparently, such behavior should not be second guessed. However, at times online tools, firm’s behaviors and human psychology result in a toxic mix. Beneficial and helpful online information should be treated with due respect as it may occasionally have surprising and harmful qualities. In this essay, we illustrate that technological changes turn the Gap into a key component in consumers' understanding, or misunderstanding, of consumer contracts. In short, a Gap may distort consumers’ perception and undermine rational decision-making. Consequently, this essay explores whether, counter-intuitively, consumer law should sanction firms that create a Gap and use it. It examines when firms’ leniency should be considered as manipulative or exercised in bad faith. It then investigates whether firms should be allowed to enforce the written contract even if the firms deliberately and consistently deviated from it.

Keywords: consumer contracts, consumer protection, information flow, law and economics, law and technology, paper deal v firms' behavior

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Authors: Mohd Asrul Affendi Bin Abdullah

Abstract:

Sample size calculation is especially important for zero inflated models because a large sample size is required to detect a significant effect with this model. This paper verify how to present percentage of power approximation for categorical and then extended to zero inflated models. Wald test was chosen to determine power sample size of AIDS death rate because it is frequently used due to its approachability and its natural for several major recent contribution in sample size calculation for this test. Power calculation can be conducted when covariates are used in the modeling ‘excessing zero’ data and assist categorical covariate. Analysis of AIDS death rate study is used for this paper. Aims of this study to determine the power of sample size (N = 945) categorical death rate based on parameter estimate in the simulation of the study.

Keywords: power sample size, Wald test, standardize rate, ZINBDR

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Authors: Gerard Lawrence

Abstract:

This paper gives an in-depth discussion on Motivation in the Malaysian Armed Forces; highlighting it as a powerful and important tool upon which the well-being of an entire (or any) organization rests. It starts with the literal definition of the word and then the psychological aspects of it detailing the intricate mechanics and fundamentals in order to accurately and systematically harness it to create a motivated workforce. It then describes the types of motivation; positive and negative, its many facets and manifestation, clearly identifying each one point by point as well as drawing examples. The paper also deals with certain controversial practices like favoritism; nepotism and provides examples of military motivation both in historic and contemporary context. It strips the current system (and its flaws) to build, nurture and maintain motivation in the future. It shows how “past practice” may not necessarily be “best practice”, by providing the building blocks necessary to move forward and cautions on the inter-relation and differences between morale and motivation. As a conclusion the paper coins a theory of working in shifts for the military and urges careful research and planning as to IF this can raise if not maintain motivation in the new era.

Keywords: armed forces, Malaysia, motivation, military psychology

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Authors: Muhammad Ashfaq

Abstract:

Main theme: This prime focus of this study is on the role of digital technology in crime prevention, with special focus on Cellular Forensic Unit, Capital City Police Peshawar-Khyber Pakhtunkhwa-Pakistan. Objective(s) of the study: The prime objective of this study is to provide statistics, strategies and pattern of analysis used for crime prevention in Cellular Forensic Unit of Capital City Police Peshawar, Khyber Pakhtunkhwa-Pakistan. Research Method and Procedure: Qualitative method of research has been used in the study for obtaining secondary data from research wing and Information Technology (IT) section of Peshawar police. Content analysis was the method used for the conduction of the study. This study is delimited to Capital City Police and Cellular Forensic Unit Peshawar-KP, Pakistan. information technologies. Major finding(s): It is evident that the old traditional approach will never provide solutions for better management in controlling crimes. The best way to control crimes and promotion of proactive policing is to adopt new technologies. The study reveals that technology have transformed police more effective and vigilant as compared to traditional policing. The heinous crimes like abduction, missing of an individual, snatching, burglaries and blind murder cases are now traceable with the help of technology. Recommendation(s): From the analysis of the data, it is reflected that Information Technology (IT) expert should be recruited along with research analyst to timely assist and facilitate operational as well as investigation units of police.A mobile locator should be Provided to Cellular Forensic Unit to timely apprehend the criminals .Latest digital analysis software should be provided to equip the Cellular Forensic Unit.

Keywords: crime prevention, digital technology, pakistan, police

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