Influence of Transportation Mode to the Deterioration Rate: Case Study of Food Transport by Ship

Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing physical or chemical characteristics considerably influence the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure the stable conditions which limit deterioration, since the value of the deterioration rate could be easily influenced by the mode of transportation. The fuzzy definition of variables allows one to take these variations into account. Furthermore, an appropriate choice of the defuzzification method permits one to adapt results to real conditions as far as possible. In this article those methods which take into account the relationship between the deterioration rate of perishable goods and transportation by ship will be applied with the aim of (a) minimizing the total cost function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) improving the supply chain sustainability by reducing environmental impact and waste disposal costs.

Measurement of Operational and Environmental Performance of the Coal-Fired Power Plants in India by Using Data Envelopment Analysis

In this study, the performance analyses of the twenty five Coal-Fired Power Plants (CFPPs) used for electricity generation are carried out through various Data Envelopment Analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output (Model-1). CO2 emitted to the environment is used as the undesired output (Model-2) in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Does Material Choice Drive Sustainability of 3D Printing?

Environmental impacts of six 3D printers using various materials were compared to determine if material choice drove sustainability, or if other factors such as machine type, machine size, or machine utilization dominate. Cradle-to-grave life-cycle assessments were performed, comparing a commercial-scale FDM machine printing in ABS plastic, a desktop FDM machine printing in ABS, a desktop FDM machine printing in PET and PLA plastics, a polyjet machine printing in its proprietary polymer, an SLA machine printing in its polymer, and an inkjet machine hacked to print in salt and dextrose. All scenarios were scored using ReCiPe Endpoint H methodology to combine multiple impact categories, comparing environmental impacts per part made for several scenarios per machine. Results showed that most printers’ ecological impacts were dominated by electricity use, not materials, and the changes in electricity use due to different plastics was not significant compared to variation from one machine to another. Variation in machine idle time determined impacts per part most strongly. However, material impacts were quite important for the inkjet printer hacked to print in salt: In its optimal scenario, it had up to 1/38th the impacts coreper part as the worst-performing machine in the same scenario. If salt parts were infused with epoxy to make them more physically robust, then much of this advantage disappeared, and material impacts actually dominated or equaled electricity use. Future studies should also measure DMLS and SLS processes / materials.

Computer Assisted Learning in a Less Resource Region

Passing the entrance exam to a university is a major step in one's life. University entrance exam commonly known as Kankor is the nationwide entrance exam in Afghanistan. This examination is prerequisite for all public and private higher education institutions at undergraduate level. It is usually taken by students who are graduated from high schools. In this paper, we reflect the major educational school graduates issues and propose ICT-based test preparation environment, known as ‘Online Kankor Exam Prep System’ to give students the tools to help them pass the university entrance exam on the first try. The system is based on Intelligent Tutoring System (ITS), which introduced an essential package of educational technology for learners that features: (I) exam-focused questions and content; (ii) self-assessment environment; and (iii) test preparation strategies in order to help students to acquire the necessary skills in their carrier and keep them up-to-date with instruction.

Particle Concentration Distribution under Idling Conditions in a Residential Underground Garage

Particles exhausted from cars have adverse impacts on human health. The study developed a three-dimensional particle dispersion numerical model including particle coagulation to simulate the particle concentration distribution under idling conditions in a residential underground garage. The simulation results demonstrate that particle disperses much faster in the vertical direction than that in horizontal direction. The enhancement of particle dispersion in the vertical direction due to the increase of cars with engine running is much stronger than that in the car exhaust direction. Particle dispersion from each pair of adjacent cars has little influence on each other in the study. Average particle concentration after 120 seconds exhaust is 1.8-4.5 times higher than the initial total particles at ambient environment. Particle pollution in the residential underground garage is severe.

Construction Unit Rate Factor Modelling Using Neural Networks

Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility and overhead & profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Design Resilient Building Strategies in Face of Climate Change

Climate change confronts the built environment with many new challenges in the form of more severe and frequent hydrometeorological events. A series of strategies is proposed whereby the various aspects of buildings and their sites can be made more resilient to the effects of such events.

Environmental Policy Instruments and Greenhouse Gas Emissions: VAR Analysis

The paper examines the interaction between the environmental taxation, size of government spending on environmental protection and greenhouse gas emissions and gross inland energy consumption. The aim is to analyze the effects of environmental taxation and government spending on environmental protection as an environmental policy instruments on greenhouse gas emissions and gross inland energy consumption in the EU15. The empirical study is performed using a VAR approach with the application of aggregated data of EU15 over the period 1995 to 2012. The results provide the evidence that the reactions of greenhouse gas emission and gross inland energy consumption to the shocks of environmental policy instruments are strong, mainly in the short term and decay to zero after about 8 years. Further, the reactions of the environmental policy instruments to the shocks of greenhouse gas emission and gross inland energy consumption are also strong in the short term, however with the deferred effects. In addition, the results show that government spending on environmental protection together with gross inland energy consumption has stronger effect on greenhouse gas emissions than environmental taxes in EU15 over the examined period.

The Effects of Gender and Socioeconomic Status on Academic Motivation: The Case of Lithuania

The problematic of gender and socioeconomic status biased differences in academic motivation patterns is discussed. Gender identity is understood according to symbolic interactionism perspective: as a result of reflected appraisals, social comparisons, self-attributions, and identifications, shaped by social environment and family context. The effects of socioeconomic status on academic motivation are conceptualized according to Bourdieu’s habitus concept, reflecting the role of unconscious and internalized cultural signals, proper to low and high socioeconomic status family contexts. Since families differ by various socioeconomic features, the hypothesis about possible impact of parents’ socioeconomic status on their children’s academic motivation interfering with gender socialization effects is held. The survey, aiming to seize gender differences in academic motivation and self-recorded improvementoriented efforts as a result of socialization processes operating in the families of low and high socioeconomic status, was designed. The results of Lithuanian higher education students’ survey are presented and discussed.

FACTS Based Stabilization for Smart Grid Applications

Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PVhybrid- Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid- Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6- pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Role of Biorefining and Biomass Utilization in Environmental Control

The continuous decline of petroleum and natural gas reserves and non linear rise of oil price has brought about a realisation of the need for a change in our perpetual dependence on the fossil fuel. A day to day increased consumption of crude and petroleum products has made a considerable impact on our foreign exchange reserves. Hence, an alternate resource for the conversion of energy (both liquid and gas) is essential for the substitution of conventional fuels. Biomass is the alternate solution for the present scenario. Biomass can be converted into both liquid as well as gaseous fuels and other feedstocks for the industries.

Malicious Route Defending Reliable-Data Transmission Scheme for Multi Path Routing in Wireless Network

Securing the confidential data transferred via wireless network remains a challenging problem. It is paramount to ensure that data are accessible only by the legitimate users rather than by the attackers. One of the most serious threats to organization is jamming, which disrupts the communication between any two pairs of nodes. Therefore, designing an attack-defending scheme without any packet loss in data transmission is an important challenge. In this paper, Dependence based Malicious Route Defending DMRD Scheme has been proposed in multi path routing environment to prevent jamming attack. The key idea is to defend the malicious route to ensure perspicuous transmission. This scheme develops a two layered architecture and it operates in two different steps. In the first step, possible routes are captured and their agent dependence values are marked using triple agents. In the second step, the dependence values are compared by performing comparator filtering to detect malicious route as well as to identify a reliable route for secured data transmission. By simulation studies, it is observed that the proposed scheme significantly identifies malicious route by attaining lower delay time and route discovery time; it also achieves higher throughput.

The Effect of Global Solar Variations on the Performance of n-AlGaAs/p-GaAs Solar Cells

This study investigates how AlGaAs/GaAs thin film solar cells perform under varying global solar spectrum due to the changes of environmental parameters such as the air mass and the atmospheric turbidity. The solar irradiance striking the solar cell is simulated using the spectral irradiance model SMARTS2 (Simple Model of the Atmospheric Radiative Transfer of Sunshine) for clear skies on the site of Setif (Algeria). The results show a reduction in the short circuit current due to increasing atmospheric turbidity, it is 63.09% under global radiation. However increasing air mass leads to a reduction in the short circuit current of 81.73%. The efficiency decreases with increasing atmospheric turbidity and air mass.

Prediction Compressive Strength of Self-Compacting Concrete Containing Fly Ash Using Fuzzy Logic Inference System

Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Fuzzy Inference System (FIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, superplasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Semiconductor Supported Gold Nanoparticles for Photodegradation of Rhodamine B

Rhodamine B (RB) is a toxic dye used extensively in textile industry, which must be remediated before its drainage to environment. In the present study, supported gold nanoparticles on commercially available titania and zincite were successfully prepared and then their activity on the photodegradation of RB under UV A light irradiation were evaluated. The synthesized photocatalysts were characterized by ICP, BET, XRD, and TEM. Kinetic results showed that Au/TiO2 was an inferior photocatalyst to Au/ZnO. This observation could be attributed to the strong reflection of UV irradiation by gold nanoparticles over TiO2 support.

Eco-Friendly Preservative Treated Bamboo Culm: Compressive Strength Analysis

Bamboo is extensively used in construction industry. Low durability of bamboo due to fungus infestation and termites attack under storage puts certain constrains for it usage as modern structural material. Looking at many chemical formulations for bamboo treatment leading to severe harmful environment effects, research on eco-friendly preservatives for bamboo treatment has been initiated world-over. In the present studies, eco-friendly preservative for bamboo treatment has been developed. To validate its application for structural purposes, investigation of effect of treatment on compressive strength has been investigated. Neemoil (25%) integrated with copper naphthenate (0.3%) on dilution with kerosene oil impregnated into bamboo culm at 2 bar pressure, has shown weight loss of only 3.15% in soil block analysis method. The results from compressive strength analysis using HEICO Automatic Compression Testing Machine reveal that preservative treatment has not altered the structural properties of bamboo culms. Compressive strength of control (11.72 N/mm2) and above treated samples (11.71 N/mm2) was found to be comparable.

Use of Hair as an Indicator of Environmental Lead Pollution: Characteristics and Seasonal Variation of Lead Pollution in Egypt

Lead being a toxic heavy metal that mankind is exposed to the highest levels of this metal from environmental pollutants. A total of 180 Male scalp hair samples were collected from different environments in Greater Cairo (GC), i.e. industrial, heavy traffic and rural areas (60 samples from each) having different activities during the period of, 1/5/2010 to 1/11/2012. Hair samples were collected during five stages. Data proved that the concentration of lead in male industrial areas of Cairo ranged between 6.2847 to 19.0432 μg/g, with mean value of 12.3288 μg/g. On the other hand, lead content of hair samples of residential-traffic areas ranged between 2.8634 to 16.3311 μg/g with mean value of 9.7552 μg/g. While lead concentration on the hair of the male residents living in rural area ranged between 1.0499-9.0402μg/g with mean value of 4.7327 μg/g. The Pb concentration in scalp hair of Cairo residents of residential-traffic and rural traffic areas was observed to follow the same pattern. The pattern was that of decrease concentration of summer and its increase in winter. Then, there was a marked increase in Pb concentration of summer 2012, and this increase was significant. These were obviously seen for the residential-traffic and rural areas residents. Pb pollution in residents of industrial areas showed the same seasonal pattern, but there was marked to decrease in Pb concentration of summer 2012, and this decrease was significant. Lead pollution in residents of GC was serious. It is worth noting that the atmosphere is still contaminated by lead despite a decade of using unleaded gasoline. Strong seasonal variation in higher Pb concentration on winter than in summer was found. Major contributions to the pollution with Pb could include industry emissions, motor vehicle emissions and long transported dust from outside Cairo. More attention should be paid to the reduction of Pb content of the urban aerosol and to the Pb pollution health.

Comparison of GSA, SA and PSO Based Intelligent Controllers for Path Planning of Mobile Robot in Unknown Environment

Now-a-days autonomous mobile robots have found applications in diverse fields. An autonomous robot system must be able to behave in an intelligent manner to deal with complex and changing environment. This work proposes the performance of path planning and navigation of autonomous mobile robot using Gravitational Search Algorithm (GSA), Simulated Annealing (SA) and Particle Swarm optimization (PSO) based intelligent controllers in an unstructured environment. The approach not only finds a valid collision free path but also optimal one. The main aim of the work is to minimize the length of the path and duration of travel from a starting point to a target while moving in an unknown environment with obstacles without collision. Finally, a comparison is made between the three controllers, it is found that the path length and time duration made by the robot using GSA is better than SA and PSO based controllers for the same work.

Decision Making about the Environmental Management Implementation – Incentives and Expectations

Environmental management implementation is presently one of the ways of organization success and value improvement. Increasing an organization motivation to environmental measures introduction is caused primarily by the rising pressure of the society that generates various incentives to endeavor for the environmental performance improvement. The aim of the paper is to identify and characterize the key incentives and expectations leading organizations to the environmental management implementation. The author focuses on five businesses of different size and field, operating in the Czech Republic. The qualitative approach and grounded theory procedure are used in research. The results point out that the significant incentives for environmental management implementation represent primarily demands of customers, the opportunity to declare the environmental commitment and image improvement. The researched enterprises less commonly expect the economical contribution, competitive advantage increase or export rate improvement. The results show that marketing contributions are primarily expected from the environmental management implementation.

Underneath Vehicle Inspection Using Fuzzy Logic, Subsumption and OpenCV Library

The inspection of underneath vehicle system has been given significant attention by governments after the threat of terrorism become more prevalent. New technologies such as mobile robots and computer vision are led to have more secure environment. This paper proposed that a mobile robot like Aria robot can be used to search and inspect the bombs under parking a lot vehicle. This robot is using fuzzy logic and subsumption algorithms to control the robot that movies underneath the vehicle. An OpenCV library and laser Hokuyo are added to Aria robot to complete the experiment for under vehicle inspection. This experiment was conducted at the indoor environment to demonstrate the efficiency of our methods to search objects and control the robot movements under vehicle. We got excellent results not only by controlling the robot movement but also inspecting object by the robot camera at same time. This success allowed us to know the requirement to construct a new cost effective robot with more functionality.