Search results for: statistical property

Authors: Rahul Jarariya

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The textile industry uses various types of dyes and discharges a lot of highly coloured wastewater. It impacts the environment like allergic reaction, respiratory, skin problems, irritation to a mucous membrane, the upper respiratory tract has to the fore, Intoxicated dye discharges 40 to 50,000 tons with great concern. Spinel ferrites gained a lot of attention due to their wide application area from biomedical to wastewater treatment. Generally, spinel ferrite is known as M-Fe2O4. Spinel type nanoparticles possess high suspension stability. The synthesis method of Microwave solution combustion (MC) method is effective for nanoscale materials, including oxides, metals, alloys, and sulfides, works as fast and energy-efficient during the process. The review focuses on controlling, nanostructure and doping. The influence of the fuel concentration and the post-treatment temperature on the structural and magnetic properties. The effects of amounts of fuel and phase changes, particle size and shape, and magnetic properties can be characterized by various techniques. Urea is the most commonly used fuel. Ethanol or n-butanol is apt for removing impurities. As a result of the materials gives fine purity. Photocatalysis phenomena act with catalyst dosage to degrade dye from wastewater. Visible light responsive produces a large amount of hydroxyl (•OH) radical made the degradation efficiency of Rh21 type dye. It develops a narrow bandgap to make it suitable for enhanced photocatalytic activity.

Keywords: microwave solution combustion method, normal spinel, doped spinels, magnetic property, Rb21

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Authors: Babak Mohajeri

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In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

Procedia PDF Downloads 317

Authors: Z. D. Mansor, C. P. Mun, B. S. Nurul Farhana, Wan Aisyah Nasuha Wan Mohamed Tarmizi

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The aim of this research is to determine the influence of transformation leadership style on employee engagement among Generation Y. The growing of Generation Y employees in Malaysia has raised concerns about how to engage and motivate this cohort. Transformation Leadership style is one of the key factors to increase employee engagement levels in the organization. This study has proven to be important for the researchers and the organization to properly understand the concept of employee engagement, transformation leadership style and their relationship. The samples in this study included 221 respondents of Generation Y who are currently working in Selangor and Klang Valley area in Malaysia. The data were collected using questionnaires and analyzed by using Statistical Package for Social Science (SPSS). The results show that there is a significant relationship between the dimension of intellectual stimulation, inspiration motivation and individual consideration on employee engagement. In contrast, the results have revealed that there is no significant relationship between idealized influences of a leader on employee engagement among Generation Y.

Keywords: employee engagement, transformational leadership styles, gen Y, survey

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Authors: Fahrudin Nugroho, Halim Hamadi, Yusril Yusuf, Pekik Nurwantoro, Ari Setiawan, Yoshiki Hidaka

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We investigate the Nikolaevskiy equation numerically using exponential time differencing method and pseudo-spectral method. This equation develops a long-wavelength modulation that behaves as a Nambu–Goldstone mode, and short-wavelength instability and exhibit turbulence. Using the autocorrelation analysis, the statistical properties of the turbulence governed by the equation are investigated. The autocorrelation then has been fitted with The Kohlrausch– Williams–Watts (KWW) expression. By varying the control parameter, we show a transition from compressed to stretched exponential for the auto-correlation function of Nikolaevskiy turbulence. The compressed exponential is an indicator of the existence of dynamical heterogeneity while the stretched indicates aging process. Thereby, we revealed the existence of dynamical heterogeneity and aging in the turbulence governed by Nikolaevskiy equation.

Keywords: compressed exponential, dynamical heterogeneity, Nikolaevskiy equation, stretched exponential, turbulence

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Authors: Salem A. Abdalla Bozrayda, Abulgasem M. Hubara

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The use of commercial poultry breeds in Libya may result in large economic losses because genotypes selected in temperate climates may respond differently to other climate conditions and management. Therefore three commercial breeds (Hypeco, Avian, and Shaver) were evaluated in two regions. The data were obtained from weekly records of three parental flocks for each breed at Ghout El-sultan and Tawargha region. Feed Hen Housed (FHH), Hen Housed Egg Production (HHEP) Mortility % were the studied traits. Statistical model include location, year, month, age and breed. Hypeco produced more HHEP 68.6 with Less FHH 22.9 kg but with higher mortility 8.5 % than Avian and shaver breeds. The breeds exhibited different responses to the different months in Libya. In conclusion, the differences, which exhibited between the breeds in traits studied, indicate that genotype x environment must be considered when select breed to perform under Libyan conditions.

Keywords: hypeco avian shaver, feed hen housed, hen housed egg production, mortility, Libya

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Authors: Neha Verma, Manik Rakhra

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Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Mutwakel Abdalla Ali Garalzain

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The aim of this study is to develop university EFL students’ communicative competence. The descriptive, analytical method was used in this study. To collect the data, the researcher designed two questionnaires, one for university EFL students and the other for English language teachers. The respondents of the study were eighty-eight; 76 university EFL students, and 12 English language teachers. The data obtained were analyzed by using statistical package for social science (SPSS). The findings of the study have revealed that most of the university EFL students are unable to express their ideas properly, although they have an abundance of vocabulary. The findings of the study have also shown that most of the university EFL students have positive attitudes towards communicative competence. The results of the study also identified the best strategies that can be used to enhance university EFL students’ communicative competence in English language teaching. The study recommends that English language textbooks should be compatible with the requirements of the student-centered approach. It also recommends that English language teachers should adopt the communicative approach’s strategies in the EFL classroom.

Keywords: applied linguistics, communicative competence , English language teaching, university EFL students

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Authors: Gajanan M. Sonwane

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The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity. This strategy of designing compounds possessing selectivity over specific tyrosine kinase has been achieved through G-QSAR and molecular docking studies. The objective of this research has been to design newer 2-phenazinamine derivatives as Bcr-Abl tyrosine kinase inhibitors by G-QSAR, molecular docking studies followed by wet-lab studies along with evaluation of their anticancer potential. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2 followed by wet-lab experiments for synthesizing 2-phenazinamine derivatives. The chemical structures of ligands in 2D were drawn by employing Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using a semi-empirical method called MOPAC. The protein structure was retrieved from RCSC protein data bank as a PDB file. The binding interactions of protein and ligands were done by using PYMOL. The molecular properties of the designed compounds were predicted in silico by using Osiris property explorer. The parent compound 2-phenazinamine was synthesized by reduction of 2, 4-dinitro-N-phenyl-benzenamine in the presence of tin chloride followed by cyclization in the presence of nitrobenzene and magnesium sulfate. The derivatization at the amino function of 2-phenazinamine was performed by treating parent compound with various aldehydes in the presence of dicyclohexylcarbodiimide (DCC) and urea to afford 2-(2-chlorophenyl)-3-(phenazine-2-yl) thiazolidine-4-one. Synthesized 39 novel derivatives of 2-phenazinamine and performed antioxidant activity, anti antiproliferative on the bulb of onion and anticancer activity on cell line showing significant competition with marked blockbuster drug imatinib.

Keywords: computer-aided drug design, tyrosin kinases, anticancer, docking

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Authors: Seyed Ali Hossein Zahraei, Iman Dianat

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The role of midwives and healthcare providers in applying pain relief methods to female patients is very important. different therapies like hydropathy, flavorer remedies, and respiratory techniques for pain relief do not work properly as what we expected. Lack of recognition of the physiological property of birth, despite findings that coming will attenuate the consequences of hurting, suggests the necessity for bigger awareness among expectant oldsters, educators, and health professionals of the potential of coming as a way of pain relief. Method: In our method we have 5 steps to achieve activation of oxytocin and dopamine pathways in order to reduce pain in all possible fields and reasons instead of using other treatments such as chemical painkillers. Step 1: First of all the patient should start by rubbing the clitoris up and down till occurring first clitoral orgasm. Step 2: Without stop rubing clitoris the patient must continue stimulate the clitoris in different way like circular motion in clock pathway until occurring second clitoral orgasm. Step 3: Immedietly the patient can change the position from clitoris to urethral opening where vestibular glands located. In this step the patient nock the urethral area very slowly without pressure and just like touching the area till feeling want to pee. But because of activation of sympathic nerves the gi tract is inactive. Step 4: In this step the patient should apply more pressure and change the motion to circular on urethral area in which the pee sensation increase but actually it is vestibular gland fluid. The patient should release it in small amount in this step. Step 5: The last step is combination of clitoral and urethral stimulation in up and down motion that cause more pee feeling and after clitoral orgasm occurred the amount of released fluid can be about 400ml.

Keywords: female, natural, method, pain

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Authors: Tannaz Alimardani, Amirhossein Moghanian, Morteza Elsa

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Bioactive glasses (BGs) are a group of surface-reactive biomaterials used in clinical applications as implants or filler materials in the human body to repair and replace diseased or damaged bone. Sol-gel technique was employed to prepare a SiO₂-CaO-P₂O₅ glass with a nominal composition of 58S BG with the addition of Sr and Li modifiers which imparts special properties to the BG. The effect of simultaneous addition of Sr and Li on bioactivity and biocompatibility, proliferation, alkaline phosphatase (ALP) activity of osteoblast cell line MC3T3-E1 and antibacterial property against methicillin-resistant Staphylococcus aureus (MRSA) bacteria were examined. BGs were characterized by X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy before and after soaking the samples in the simulated body fluid (SBF) for different time intervals to characterize the formation of hydroxyapatite (HA) formed on the surface of BGs. Structural characterization indicated that the simultaneous presence of 5% Sr and 5% Li in 58S-BG composition not only did not retard HA formation because of the opposite effect of Sr and Li of the dissolution of BG in the SBF, but also stimulated the differentiation and proliferation of MC3T3-E1s. Moreover, the presence of Sr and Li on the dissolution of the ions resulted in an increase in the mean number of DAPI-labeled nuclei which was in good agreement with the live/dead assay. The result of antibacterial tests revealed that Sr and Li-substituted 58S bioactive glass exhibited a potential antibacterial effect against MRSA bacteria. Because of optimal proliferation and ALP activity of MC3T3-E1cells, proper bioactivity and high antibacterial potential against MRSA, BG-5/5 is suggested as a multifunctional candidate for bone tissue engineering.

Keywords: alkaline, alkaline earth, bioglass, co-doping, ion release

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Authors: Davie G. Dave, Prisca H. Mugabe, Tonderai Mutibvu

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Globally, HWCs are on the rise. Such is the case with urban areas in Zimbabwe, yet little has been documented about it. This study was done to provide insights into the occurrence of human-wildlife conflicts in urban areas. The study was carried out in Harare, Bindura, Masvingo, Beitbridge, and Chiredzi to determine the cause, nature, extent, and frequency of occurrence of HWC, to determine the key wildlife species involved in conflicts and management practices done to combat wildlife conflicts in these areas. Several sampling techniques encompassing multi-stage sampling, stratified random, purposive, and simple random sampling were employed for placing residential areas into three strata according to population density, selecting residential areas, and selecting actual participants. Data were collected through a semi-structured questionnaire and key informant interviews. The results revealed that property destruction and crop damage were the most prevalent conflicts. Of the 15 animals that were cited, snakes, baboons, and monkeys were associated with the most conflicts. The occurrence of HWCs was mainly attributed to the increase in both animal and human populations. To curtail these HWCs, the local people mainly used non-lethal methods, whilst lethal methods were used by authorities for some of the reported cases. The majority of the conflicts were seasonal and less severe. There were growing concerns by respondents on the issues of wildlife conflicts, especially in those areas that had primates, such as Warren Park in Harare and Limpopo View in Beitbridge. There are HWCs hotspots in urban areas, and to ameliorate this, suggestions are that there is a need for a multi-action approach that includes general awareness campaigns on HWCs and land use planning that involves the creation of green spaces to ease wildlife management.

Keywords: human-wildlife conflicts, mitigation measures, residential areas, types of conflicts, urban areas

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Authors: Tien Hui Chiang

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Along with the predominant influence of neo-liberalism, public managerialism is viewed as a panacea for curing the institutionalized weakness caused by the monopoly of the public sector. In the name of efficiency, its outcome-led approach acquires a legitimate status and, in turn, it transforms into the discourse of performativity, reformulating the souls of individual members into the form of docile bodies who are willing to demonstrate their own ability in organizational contributions. The evaluation system and the organizational reconstruction are viewed as the crucial means for achieving this mission. Inevitably, university teachers are confined within a rigid and bureaucratic setting, in which they do not have too much latitude but are subject to the commands of senior administrators. However, the notion of duality highlights the interaction between structural constraints and agency. If the actor discovers the rules or properties of social structure, he/she is able to transform structural constraints into resources for developing creative actions, conceptualized as an agency. This study was designed for examining how duality operates within this hierarchical arrangement formed by public managerialism. Fourteen informants were interviewed from February to August 2014. The findings show that the evaluation system created the culture of neo-academicalism, addressing excellence in research and, in turn, motivating academic-oriented teachers. This correspondence provided a gateway for them to win honor, dignity, and prestige in groups. However, unlike the concept of duality, this agency was operating within the institutionalized context, regulated by structural constraint. Furthermore, complying with the rule/property of social structure was able to secure their advantages.

Keywords: public managerialism, social discourse, neo-academicalism, duality, structural constraint, agency

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Authors: Manar Aslan, Ayfer Karaaslan

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Purpose: The aim of this study was to determine the attitude towards the use of the maiden name of the Turkish people. Methods: For the study group who lives in the center of Konya/Turkey and people aged 16-65 years, as the sample identified 1,000 people with simple random between the months of February to May 2013. The survey created by the researchers, for investigating the perception of using the maiden name of the people of Konya consists of 25 questions with demographic characteristics. For statistical analysis of the obtained data made using SPSS 20, chi-square test and one-way analysis of variance methods of frequency, average, were evaluated as percentage distribution. Results: The traditional view of Konya increasing age increases, decreases the desire to use her maiden name. So look favorably than younger generations to use maiden name. In parallel with the level of educational levels are increasing utilization rates maiden name. Thus, individuals with higher levels of education are more positive look at the use of her maiden name. Looking at the marital status; compared to individuals with a single against the use of her maiden name of individuals who are married are more negative attitude.

Keywords: Maiden name, public viewpoint, utilization, women

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Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

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Authors: Asaad Pireh

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The Zagros fold and thrust belt is one of the most active seismic zones of Iran where hosts many people and considerable oil and gas resources. The Zagros fold and thrust belt, based on its stratigraphy has been divided into three provinces. Mechanical stratigraphy of these provinces is different together. Statistical analyses all of earthquakes which has happened in the Zagros fold and thrust belt from 1964 up to December 2014, shows that strong earthquakes have occurred within the southeastern part of these subdivisions which has a smaller ratio of incompetent to competent thickness and in the northwestern part of these subdivisions which has a greater ratio of incompetent to competent thickness has occurred the weakest earthquakes. The southeastern part of the Zagros has a higher seismic risk and northwestern part of these fold belt have a lower seismic risk.

Keywords: earthquake, mechanical stratigraphy, seismic risk, Zagros

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Authors: Ehsan Alishahi, Chuang Deng

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Commercial applications of bulk metallic glasses (BMGs) were restricted due to the sudden brittle failure mode which was the main drawback in these new class of materials. Therefore, crystalline-amorphous (C-A) composites were introduced as a toughening strategy in BMGs. In spite of numerous researches in the area of metallic C-A composites, the fundamental structure-property relation in these composites that are not exactly known yet. In this study, it is aimed to investigate the fundamental properties of crystalline-amorphous interface in a model system of Cu/CuZr by using molecular dynamics simulations. Several parameters including interface energy and mechanical properties were investigated by means of atomic models and employing Embedded Atom Method (EAM) potential function. It is found that the crystalline-amorphous interfacial energy weakly depends on the orientation of the crystalline layer, which is in stark contrast to that in a regular crystalline grain boundary. Additionally, the results showed that the interface controls the yielding of the crystalline-amorphous composites during uniaxial tension either by serving as sources for dislocation nucleation in the crystalline layer or triggering local shear transformation zones in amorphous layer. The critical resolved shear stress required to nucleate the first dislocation is also found to strongly depend on the crystalline orientation. Furthermore, it is found that the interaction between dislocations and shear localization at the crystalline-amorphous interface oriented in different directions can lead to a change in the deformation mode. For instance, while the dislocation and shear banding are aligned to each other in {0 0 1} interface plane, the misorientation angle between these failure mechanisms causing more homogeneous deformation in {1 1 0} and {1 1 1} crystalline-amorphous interfaces. These results should help clarify the failure mechanism of crystalline-amorphous composites under various loading conditions.

Keywords: crystalline-amorphous, composites, orientation, plasticity

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: Dariusz Jemielniak

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The near future will bring significant changes to contemporary organizations and management, because of the rapidly increasing role of immaterial goods and knowledge workers. The area of copyright, IP, as well as digital (non-material) goods and media redistribution seems to be one of the major challenges for the economy and society in general, and management and organization studies in particular. The proposed paper shows the views and perceptions of fairness of digital media sharing among Harvard Law School LL.M. students, basing on 50 qualitative interviews and 100 questionnaires. The researcher took an ethnographic approach to the study and joined the 2016 Harvard LL.M. Facebook group, which allowed natural socializing and joining for in-person events and private parties more easily. After making acquaintance with many of the students, the researcher conducted a quantitative questionnaire with 100 respondents, allowing to better understand the respondents perception of fairness in digital files sharing in different contexts (depending on the price of the media, its availability, regional licensing, status of the copyright holder, etc.). Basing on the results of the questionnaire, the researcher followed up with long-term, open ended, loosely structured ethnographic interviews (50 interviews were conducted) to further deepen the understanding of the results. The major finding of the study is that Harvard lawyers, in spite of the highest possible understanding of law, as well as professional standards, generally approve of digital piracy in certain contexts. Interestingly, they are also more likely to approve of it if they work for the government rather than the private sector. The conclusions from this study allow a better understanding of how ‘fairness’ is perceived by the younger generation of law professionals, and also open grounds for a more rational licensing policing.

Keywords: piracy, digital sharing, perception of fairness, legal profession

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Authors: Safak Baykal

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The purpose of this study is analyzing the relationship between self leadership and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: bonding, homophilous social capital (BoSC) which implies better, strong, dense or closed network ties, and bridging, heterophilous social capital (BrSC) which implies weak ties, bridging the structural holes. The other concept of the study is Trust (Tr), namely interpersonal trust, willingness to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.73 and social capital values (BoSC/BrSC) is highly correlated with Tr values of the people.

Keywords: bonding social capital, bridging social capital, trust, social network analysis (SNA)

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Authors: Humera Malik

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Gender inequality, as a societal issue, is prevalent in all spheres of life in Pakistan. It is world-wide understood that gender equality is a basic right of every human being as well as the source of development and prosperity for the whole country. In fact, many countries endeavor to ensure equal opportunities for men and women which will, in turn, help to attain sustainable growth in every field. Most of the women in Pakistan live their life under the societal pressure which is exerted by centuries old traditions. This archaic setup restricts women to stay at home because their survival is conditional to their total subjugation to the male member of the family. This patriarchal structure confers men the right to deal women as their property. It is not wrong to say that women endure severe discrimination in their whole life. No doubt, women are confronted with multifaceted discrimination in the field of education, health, politics, social status, etc. The main theme of this research is to ascertain the present condition of gender inequality in the field of economy in Pakistan. Pakistan’s poor ranking in Global Gender Gap Index, 2016 clearly depicts that women are deprived of fundamental rights as well as equal opportunities of development. This very state of affairs depicts the real picture of government’s commitment to women empowerment and gender equality. The nature of this research is descriptive which helps to determine the status of women in Pakistan on the basis of labour force participation, wage gap, estimated incomes, and ratio of high ranking positions secured by women. It is an endeavor to understand the reasons of economic inequality by following qualitative method of research. Moreover, few recommendations will be suggested to get rid of this issue.

Keywords: dismal, discrimination, feudal, patriarchal, wage gap

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Authors: T. Godwin

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The design of a supply chain always entails the trade-off between responsiveness and efficiency. The launch of e-commerce has not only changed the way of shopping but also altered the supply chain design while trading off efficiency with responsiveness. A concept called ‘virtual responsiveness’ is introduced in the context of e-commerce supply chain. A simulation model is developed to compare actual responsiveness and virtual responsiveness to the customer in an e-commerce supply chain. The simulation is restricted to the movement of goods from the e-tailer to the customer. Customer demand follows a statistical distribution and is generated using inverse transformation technique. The two responsiveness schemes of the supply chain are compared in terms of the minimum number of inventory required at the e-tailer to fulfill the orders. Computational results show the savings achieved through virtual responsiveness. The insights gained from this study could be used to redesign e-commerce supply chain by incorporating virtual responsiveness. A part of the achieved cost savings could be passed back to the customer, thereby making the supply chain both effective and competitive.

Keywords: e-commerce, simulation modeling, supply chain, virtual responsiveness

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Authors: Yan-Ren Chen, Jenn-Kaie Lain

Abstract:

This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

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Authors: Rema Daher, Theodor Chakhachiro, Daniel Asmar

Abstract:

In the era of autonomous robot mapping, assessing the goodness of the generated maps is important, and is usually performed by aligning them to ground truth. Map alignment is difficult for two reasons: first, the query maps can be significantly distorted from ground truth, and second, establishing what constitutes ground truth for different settings is challenging. Most map alignment techniques to this date have addressed the first problem, while paying too little importance to the second. In this paper, we propose a benchmark dataset, which consists of synthetically transformed maps with their corresponding displacement fields. Furthermore, we propose a new system for comparison, where the displacement field of any map alignment technique can be computed and compared to the ground truth using statistical measures. The local information in displacement fields renders the evaluation system applicable to any alignment technique, whether it is linear or not. In our experiments, the proposed method was applied to different alignment methods from the literature, allowing for a comparative assessment between them all.

Keywords: assessment methods, benchmark, image deformation, map alignment, robot mapping, robot motion

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

Abstract:

Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Alam Ali, Ashok Kumar Pathak

Abstract:

Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Akhatjon Nasullaev, Raffaella Manzini, Vincent Frigant

Abstract:

The prior research largely discussed open innovation practices both in large and small and medium-sized enterprises (SMEs). Open Innovation compels firms to observe and analyze the external environment in order to tap new opportunities for inbound and/or outbound flows of knowledge, ideas, work in progress innovations. As SMEs are different from their larger counterparts, they face several limitations in utilizing open innovation activities, such as resource scarcity, unstructured innovation processes and underdeveloped innovation capabilities. Technology intelligence – the process of systematic acquisition, assessment and communication of information about technological trends, opportunities and threats can mitigate this limitation by enabling SMEs to identify technological and market opportunities in timely manner and undertake sound decisions, as well as to realize a ‘first mover advantage’. Several studies highlighted firm-level barriers to successful implementation of open innovation practices in SMEs, namely challenges in partner selection, intellectual property rights and trust, absorptive capacity. This paper aims to investigate the question how technology intelligence can be useful for SMEs to overcome the barriers to effective open innovation. For this, we conduct a case study in four Estonian life-sciences SMEs. Our findings revealed that technology intelligence can support SMEs not only in inbound open innovation (taking into account inclination of most firms toward technology exploration aspects of open innovation) but also outbound open innovation. Furthermore, the results of this study state that, although SMEs conduct technology intelligence in unsystematic and uncoordinated manner, it helped them to increase their innovative performance.

Keywords: technology intelligence, open innovation, SMEs, life sciences

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Authors: Vikrant Gupta, Amrit Goswami

Abstract:

The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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