Search results for: principal objects

Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Fayyaz Rasool, Naureen Aziz Qureshi, Shakeela Parveen

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Labeo rohita populations from five geographical locations from the hatchery and riverine system of Punjab-Pakistan were studied for the clustering on the basis of similarities and differences based on morphometric parameters within the species. Agglomerative Hierarchical Clustering (AHC) was done by using Pearson Correlation Coefficient and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as Agglomeration method by XLSTAT 2012 version 1.02. A dendrogram with the data on the morphometrics of the representative samples of each site divided the populations of Labeo rohita in to five major clusters or classes. The variance decomposition for the optimal classification values remained as 19.24% for within class variation, while 80.76% for the between class differences. The representative central objects of the each class, the distances between the class centroids and also the distance between the central objects of the classes were generated by the analysis. A measurable distinction between the classes of the populations of the Labeo rohita was indicated in this study which determined the impacts of changing environment and other possible factors influencing the variation level among the populations of the same species.

Keywords: AHC, Labeo rohita, hatchery, riverine, morphometric

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

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Changes in the global risk appetite cause co-movement in emerging market risk premiums. However, the sensitivity of the changes in risk premium to the global risk appetite may vary across emerging markets. In this study, how the global risk appetite affects Credit Default Swap (CDS) premiums in emerging markets are analyzed using Principal Component Analysis (PCA) and rolling regressions. The PCA results indicate that the first common component derived by the PCA accounts for almost 76 percent of the common variation in CDS premiums. Additionally, the explanatory power of the first factor seems to be high over the sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are used to identify the macroeconomic factors driving the heterogeneity across emerging markets. The panel regression results point to the significance of government debt to GDP and international reserves to GDP in explaining sensitivity. Accordingly, countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: credit default swaps, emerging markets, principal components analysis, sovereign risk

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Authors: Al. Tsertsvadze. L. Ebralidze, I. Matchutadze. D. Berashvili, A. Bakuridze

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Peatlands are landscape elements, they are formed over a very long period by physical, chemical, biologic, and geologic processes. In the moderate zone of Caucasus, the Kolkheti lowlands are distinguished by the diversity of relictual plants, a high degree of endemism, orographic, climate, landscape, and other characteristics of high levels of biodiversity. The unique properties of the Kolkheti region lead to the formation of special, so-called, endemic peat peloids. The composition and properties of peloids strongly depend on peat-forming plants. Peat is considered a unique complex of raw materials, which can be used in different fields of the industry: agriculture, metallurgy, energy, biotechnology, chemical industry, health care. They are formed in permanent wetland areas. As a result of decay, higher plants remain in the anaerobic area, with the participation of microorganisms. Peat mass absorbs soil and groundwater. Peloids are predominantly rich with humic substances, which are characterized by high biological activity. Humic acids stimulate enzymatic activity, regenerative processes, and have anti-inflammatory activity. Objects of the research were Kolkheti peat peloids (Ispani, Anaklia, Churia, Chirukhi, Peranga) possessing different formation phases. Due to specific physical and chemical properties of research objects, the aim of the research was to develop analytical methods in order to study the chemical composition of the objects. The research was held using modern instrumental methods of analysis: Ultraviolet-visible spectroscopy and Infrared spectroscopy, Scanning Electron Microscopy, Centrifuge, dry oven, Ultraturax, pH meter, fluorescence spectrometer, Gas chromatography-mass spectrometry (GC-MS/MS), Gas chromatography. Based on the research ration between organic and inorganic substances, the spectrum of micro and macro elements, also the content of minerals was determined. The content of organic nitrogen was determined using the Kjeldahl method. The total composition of amino acids was studied by a spectrophotometric method using standard solutions of glutamic and aspartic acids. Fatty acid was determined using GC (Gas chromatography). Based on the obtained results, we can conclude that the method is valid to identify fatty acids in the research objects. The content of organic substances in the research objects was held using GC-MS. Using modern instrumental methods of analysis, the chemical composition of research objects was studied. Each research object is predominantly reached with a broad spectrum of organic (fatty acids, amino acids, carbocyclic and heterocyclic compounds, organic acids and their esters, steroids) and inorganic (micro and macro elements, minerals) substances. Modified methods used in the presented research may be utilized for the evaluation of cosmetological balneological and pharmaceutical means prepared on the base of Kolkheti's Sphagnum Peat Peloids.

Keywords: modern analytical methods, natural resources, peat, chemistry

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

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Risk premium of emerging markets are moving altogether depending on the momentum and shifts in the global risk appetite. However, the magnitudes of these changes in the risk premium of emerging market economies might vary. In this paper, we focus on how global risk factor affects credit default swaps (CDS) premiums of emerging markets using principal component analysis (PCA) and rolling regressions. PCA results indicate that the first common component accounts for almost 76% of common variation in CDS premiums of emerging markets. Additionally, the explanatory power of the first factor seems to be high over sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are employed to identify the macroeconomic factors driving the heterogeneity across emerging markets. There are two main macroeconomic variables that affect the sensitivity; government debt to GDP and international reserves to GDP. The countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: emerging markets, principal component analysis, credit default swaps, sovereign risk

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Authors: Khin Khin Thant Sin

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This study is a case study which investigates successful and ongoing bottom-up innovations for school improvement initiatives in Hungary. Two innovative schools are selected in this study due to their outstanding achievement during the past ten years in Hungary. In one school, data from the personal experiences of a school principal who initiated the bottom-up innovation are included. For the second school, three interviews were carried out with two schoolteachers and one secondary school student. In addition, desk research, including the principal’s published articles, the schoolteachers’ master thesis, the school websites, and other published articles, are analysed to explore the schools’ innovative processes. This study investigates how bottom-up innovation led to major achievements in student learning, teacher professional development, networking and collaboration with other schools, and the establishment of successful partnerships with universities. The highlight of this study is how innovative schools can be the major sources promoting educational innovations as well as improving teacher education, especially in initial teacher education and continuous professional development.

Keywords: school innovation, teacher education, hungary, educational innovation, school improvement

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Authors: I. Filikhin, B. Vlahovic

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We focus on a novel type of detection based on electron tunneling properties of double nanoscale structures in semiconductor materials. Semiconductor heterostructures as quantum wells (QWs), quantum dots (QDs), and quantum rings (QRs) may have energy level structure of several hundred of electron confinement states. The single electron spectra of the double quantum objects (DQW, DQD, and DQR) were studied in our previous works with relation to the electron localization and tunneling between the objects. The wave function of electron may be localized in one of the QDs or be delocalized when it is spread over the whole system. The localizing-delocalizing tunneling occurs when an electron transition between both states is possible. The tunneling properties of spectra differ strongly for “regular” and “chaotic” systems. We have shown that a small violation of the geometry drastically affects localization of electron. In particular, such violations lead to the elimination of the delocalized states of the system. The same symmetry violation effect happens if electrical or magnetic fields are applied. These phenomena could be used to propose a new type of detection based on the high sensitivity of charge transport between double nanostructures and small violations of the shapes. It may have significant technological implications.

Keywords: double quantum dots, single electron levels, tunneling, electron localizations

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Authors: Rafay Ahmed, Condon Lau

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Bone healing is a complex and sequential process involving changes at the molecular level. Raman spectroscopy is a promising technique to study bone mineral and matrix environments simultaneously. In this study, subcritical calvarial defects are used to study bone composition during healing without discomposing the fracture. The model allowed to monitor the natural healing of bone avoiding mechanical harm to the callus. Calvarial defects were created using 1mm burr drill in the parietal bones of Sprague-Dawley rats (n=8) that served in vivo defects. After 7 days, their skulls were harvested after euthanizing. One additional defect per sample was created on the opposite parietal bone using same calvarial defect procedure to serve as control defect. Raman spectroscopy (785 nm) was established to investigate bone parameters of three different skull surfaces; in vivo defects, control defects and normal surface. Principal component analysis (PCA) was utilized for the data analysis and interpretation of Raman spectra and helped in the classification of groups. PCA was able to distinguish in vivo defects from normal surface and control defects. PC1 shows that the major variation at 958 cm⁻¹, which corresponds to ʋ1 phosphate mineral band. PC2 shows the major variation at 1448 cm⁻¹ which is the characteristic band of CH2 deformation and corresponds to collagens. Raman parameters, namely, mineral to matrix ratio and crystallinity was found significantly decreased in the in vivo defects compared to surface and controls. Scanning electron microscope and optical microscope images show the formation of newly generated matrix by means of bony bridges of collagens. Optical profiler shows that surface roughness increased by 30% from controls to in vivo defects after 7 days. These results agree with Raman assessment parameters and confirm the new collagen formation during healing.

Keywords: Raman spectroscopy, principal component analysis, calvarial defects, tissue characterization

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Authors: Prachyanun Nilsook, Panita Wannapiroon

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The purpose of this research is to study a Digital Learning Repository System (DLRS) on vocational teachers and teaching in Thailand. The innobpcd.net is a DLRS being utilized by the Office of Vocational Education Commission and operationalized by the Bureau of Personnel Competency Development for vocational education teachers. The aim of the system is to support and enhance the process of vocational teaching and to improve staff development by providing teachers with a variety of network connections and information. The system provides centralized hosting and access to content, and the ability to share digital objects or files, to set permissions and controls for access to content that can be used vocational education teachers for their teaching and for their own development. The elements of DLRS include; Digital learning system, Media Library, Knowledge-based system and Mobile Application. The system aims to link vocational teachers to the most effective emerging technologies available for learning, so they are better resourced to support their vocational students. The initial results from this evaluation indicate that there is a range of services provided by the system being used by vocational teachers and this paper indicates which facilities have the greatest usage and impact on vocational teaching in Thailand.

Keywords: digital learning repositories, vocational education, knowledge sharing, learning objects

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Taher Abofol, Eldad Yechiam, Thorsten Pachur

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In four studies, we examined whether seller and buyers differ not only in subjective price levels for objects (i.e., the endowment effect) but also in their relative accuracy given objects varying in expected value. If, as has been proposed, sellers stand to accrue a more substantial loss than buyers do, then their pricing decisions should be more sensitive to expected-value differences between objects. This is implied by loss aversion due to the steeper slope of prospect theory’s value function for losses than for gains, as well as by loss attention account, which posits that losses increase the attention invested in a task. Both accounts suggest that losses increased sensitivity to relative values of different objects, which should result in better alignment of pricing decisions to the objective value of objects on the part of sellers. Under loss attention, this characteristic should only emerge under certain boundary conditions. In Study 1 a published dataset was reanalyzed, in which 152 participants indicated buying or selling prices for monetary lotteries with different expected values. Relative EV sensitivity was calculated for participants as the Spearman rank correlation between their pricing decisions for each of the lotteries and the lotteries' expected values. An ANOVA revealed a main effect of perspective (sellers versus buyers), F(1,150) = 85.3, p < .0001 with greater EV sensitivity for sellers. Study 2 examined the prediction (implied by loss attention) that the positive effect of losses on performance emerges particularly under conditions of time constraints. A published dataset was reanalyzed, where 84 participants were asked to provide selling and buying prices for monetary lotteries in three deliberations time conditions (5, 10, 15 seconds). As in Study 1, an ANOVA revealed greater EV sensitivity for sellers than for buyers, F(1,82) = 9.34, p = .003. Importantly, there was also an interaction of perspective by deliberation time. Post-hoc tests revealed that there were main effects of perspective both in the condition with 5s deliberation time, and in the condition with 10s deliberation time, but not in the 15s condition. Thus, sellers’ EV-sensitivity advantage disappeared with extended deliberation. Study 3 replicated the design of study 1 but administered the task three times to test if the effect decays with repeated presentation. The results showed that the difference between buyers and sellers’ EV sensitivity was replicated in repeated task presentations. Study 4 examined the loss attention prediction that EV-sensitivity differences can be eliminated by manipulations that reduce the differential attention investment of sellers and buyers. This was carried out by randomly mixing selling and buying trials for each participant. The results revealed no differences in EV sensitivity between selling and buying trials. The pattern of results is consistent with an attentional resource-based account of the differences between sellers and buyers. Thus, asking people to price, an object from a seller's perspective rather than the buyer's improves the relative accuracy of pricing decisions; subtle changes in the framing of one’s perspective in a trading negotiation may improve price accuracy.

Keywords: decision making, endowment effect, pricing, loss aversion, loss attention

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Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

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Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: augmented reality, e-learning, marker-based, monitor-based

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Authors: Kien Tsong Chau, Zarina Samsudin, Wan Ahmad Jaafar Wan Yahaya

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The paper examined the capability of a prototype of a tangible multimedia system that was augmented with tangible objects in motivating young preschoolers in learning. Preschoolers’ learning behaviour is highly captivated and motivated by external physical stimuli. Hence, conventional multimedia which solely dependent on digital visual and auditory formats for knowledge delivery could potentially place them in inappropriate state of circumstances that are frustrating, boring, or worse, impede overall learning motivations. This paper begins by discussion with the objectives of the research, followed by research questions, hypotheses, ARCS model of motivation adopted in the process of macro-design, and the research instrumentation, Persuasive Multimedia Motivational Scale was deployed for measuring the level of motivation of subjects towards the experimental tangible multimedia. At the close, a succinct description of the findings of a relevant research is provided. In the research, a total of 248 preschoolers recruited from seven Malaysian kindergartens were examined. Analyses revealed that the tangible multimedia system improved preschoolers’ learning motivation significantly more than conventional multimedia. Overall, the findings led to the conclusion that the tangible multimedia system is a motivation conducive multimedia for preschoolers.

Keywords: tangible multimedia, preschoolers, multimedia, tangible objects

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Authors: Helle Nissen

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Physical objects surrounding people in healthcare environments are carriers of institutional logics materialized into the objects by its producers. However, institutional logics research lacks to inform us how logics become materialized and are perceived by producers vs. users of an object. The study is based on a 3-year longitudinal case study of a Danish Public Private Innovation project aiming to co-create an innovative healthcare bed commercialized to public psychiatric hospitals. The producers are a private metal firm and industrial designers from two Danish regions. The findings demonstrate that the metal firm and designers, as producers, negotiate about materializing different logics into the bed throughout the innovation process. An aesthetic logic is prioritized most, and the producers encode it with the intention to develop a bed that looks homely and less hospital-like compared to previous and existing healthcare beds. After the bed is put into use, the aesthetic logic is decoded by the users. Their perception of it differs significantly from the producers’ intended meaning, as the healthcare bed is perceived as sterile. The study has theoretical implications: It demonstrates how logics become materialized ‘here and now’, and it reveals logics as less governed by stable and clear meanings but rather as subject to changeable perceptions.

Keywords: co-creation, healthcare innovation, commercialization, institutional logics

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Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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Authors: Aboubakr Gambo, Adama Diaw, Tobias Wunscher

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This study attempts to identify factors affecting rural households’ resilience to food insecurity in Niger. For this, we first create a resilience index by using Principal Component Analysis on the following five variables at the household level: income, food expenditure, duration of grain held in stock, livestock in Tropical Livestock Units and number of farms exploited and second apply Structural Equation Modelling to identify the determinants. Data from the 2010 National Survey on Households’ Vulnerability to Food Insecurity done by the National Institute of Statistics is used. The study shows that asset and social safety nets indicators are significant and have a positive impact on households’ resilience. Climate change approximated by long-term mean rainfall has a negative and significant effect on households’ resilience to food insecurity. The results indicate that to strengthen households’ resilience to food insecurity, there is a need to increase assistance to households through social safety nets and to help them gather more resources in order to acquire more assets. Furthermore, early warning of climatic events could alert households especially farmers to be prepared and avoid important losses that they experience anytime an uneven climatic event occur.

Keywords: food insecurity, principal component analysis, structural equation modelling, resilience

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Authors: Mojtaba Eshraghi Arani

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The freight forwarders, who are known as the Architect of Transportation, play a vital role in the supply chain management. The package of various services which they provide has made the legal nature of freight forwarders very controversial, so that they might be qualified once as principal or carrier and, on other occasions, as agent of the shipper as the case may be. They could even be involved in the transportation process as the agent of shipping line, which makes the situation much more complicated. The courts in all countries have long had trouble in distinguishing the “forwarder as agent” from “forwarder as principal” (as it is outstanding in the prominent case of “Vastfame Camera Ltd v Birkart Globistics Ltd And Others” 2005, Hong Kong). It is not fully known that in the case of a claim against the forwarder, what particular parameter would be used by the judge among multiple, and sometimes contradictory, tests for determining the scope of the forwarder liability. In particular, every country has its own legal parameters for qualifying the freight forwarders that is completely different from others, as it is the case in France in comparison with Germany and England. The unpredictability of the courts’ decisions in this regard has provided the freight forwarders with the opportunity to impose any limitation or exception of liability while pretending to play the role of a principal, consequently making the cargo interests incur ever-increasing damage. The transportation industry needs to remove such uncertainty by unifying national laws governing freight forwarders liability. A long time ago, in 1967, The International Institute for Unification of Private Law (UNIDROIT) prepared a draft convention called “Draft Convention on Contract of Agency for Forwarding Agents Relating to International Carriage of Goods” (hereinafter called “UNIDROIT draft convention”). The UNIDROIT draft convention provided a clear and certain framework for the liability of freight forwarder in each capacity as agent or carrier, but it failed to transform to a convention, and eventually, it was consigned to oblivion. Today, after nearly 6 decades from that era, the necessity of such convention can be felt apparently. However, one might reason that the same grounds, in particular, the resistance by forwarders’ association, FIATA, exist yet, and thus it is not logical to revive a forgotten draft convention after such long period of time. It is argued in this article that the main reason for resisting the UNIDROIT draft convention in the past was pending efforts for developing the “1980 United Nation Convention on International Multimodal Transport of Goods”. However, the latter convention failed to become in force on due time in a way that there was no new accession since 1996, as a result of which the UNIDROIT draft convention must be revived strongly and immediately submitted to the relevant diplomatic conference. A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and cases.

Keywords: freight forwarder, revival, agent, principal, uidroit, draft convention

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Authors: Carmela Perta

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In Italy the coexistence of standard language, its varieties and different minority languages - historical and migration languages - has been a way to study language contact in different directions; the focus of most of the studies is either the relations among the languages of the social repertoire, or the study of contact phenomena occurring in a particular structural level. However, studies on contact facts in relation to a given sociolinguistic situation of the speech community are still not present in literature. As regard the language level to investigate from the perspective of contact, it is commonly claimed that the lexicon is the most volatile part of language and most likely to undergo change due to superstrate influence, indeed first lexical features are borrowed, then, under long term cultural pressure, structural features may also be borrowed. The aim of this paper is to analyse language contact in two historical minority communities where Francoprovençal is spoken, in relation to their sociolinguistic situation. In this perspective, firstly lexical borrowings present in speakers’ speech production will be examined, trying to find a possible correlation between this part of the lexicon and informants’ sociolinguistic variables; secondly a possible correlation between a particular community sociolinguistic situation and lexical borrowing will be found. Methods used to collect data are based on the results obtained from 24 speakers in both the villages; the speaker group in the two communities consisted of 3 males and 3 females in each of four age groups, ranging in age from 9 to 85, and then divided into five groups according to their occupations. Speakers were asked to describe a sequence of pictures naming common objects and then describing scenes when they used these objects: they are common objects, frequently pronounced and belonging to semantic areas which are usually resistant and which are thought to survive. A subset of this task, involving 19 items with Italian source is examined here: in order to determine the significance of the independent variables (social factors) on the dependent variable (lexical variation) the statistical package SPSS, particularly the linear regression, was used.

Keywords: borrowing, Francoprovençal, language change, lexicon

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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Authors: Zhen Sun

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The study adopts the method of visual social semiotics to analyze a sample of fashion photos that were recently published in Chinese fashion magazines that target towards both male and female readers. It identifies a new visual trend in fashion photography, which is characterized by two features. First, the photos represent young, confident, and stylish female models with lower-class sloppy old men. The visual inharmony between the sexually desirable women and the aged men has suggested an impossibly accomplished sexuality and eroticism. Though the women are still under the male gaze, they are depicted as unreachable objects of voyeurism other than sexual objects subordinated to men. Second, the represented people are usually put in the backdrop of tasteless or vulgar Chinese town life, which is congruent with the images of men but makes the modern city girls out of place. The photographers intentionally contrast the images of women with that of men and with the background, which implies an imaginary binary division of modern Orientalism and the photographers’ self-orientalization strategy. Under the theoretical umbrella of neoliberal postfeminism, this study defines a new kind of gynocentric stereotype in Chinese fashion photography, which challenges the previous observations on gender portrayals in fashion magazines.

Keywords: fashion photography, gynocentrism, neoliberal postfeminism, self-orientalization

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Authors: Getachew Weldemichael, Sentayehu Alamerew, Leta Tulu, Gezahegn Berecha

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Coffee quality improvement program is becoming the focus of coffee research, as the world coffee consumption pattern shifted to high-quality coffee. However, there is limited information on the genetic variation of C. Arabica for quality improvement in potential specialty coffee growing areas of Ethiopia. Therefore, this experiment was conducted with the objectives of determining the magnitude of variation among 105 coffee accessions collected from east Wollega coffee growing areas and assessing correlations between the different coffee qualities attributes. It was conducted in RCRD with three replications. Data on green bean physical characters (shape and make, bean color and odor) and organoleptic cup quality traits (aromatic intensity, aromatic quality, acidity, astringency, bitterness, body, flavor, and overall standard of the liquor) were recorded. Analysis of variance, clustering, genetic divergence, principal component and correlation analysis was performed using SAS software. The result revealed that there were highly significant differences (P<0.01) among the accessions for all quality attributes except for odor and bitterness. Among the tested accessions, EW104 /09, EW101 /09, EW58/09, EW77/09, EW35/09, EW71/09, EW68/09, EW96 /09, EW83/09 and EW72/09 had the highest total coffee quality values (the sum of bean physical and cup quality attributes). These genotypes could serve as a source of genes for green bean physical characters and cup quality improvement in Arabica coffee. Furthermore, cluster analysis grouped the coffee accessions into five clusters with significant inter-cluster distances implying that there is moderate diversity among the accessions and crossing accessions from these divergent inter-clusters would result in hetrosis and recombinants in segregating generations. The principal component analysis revealed that the first three principal components with eigenvalues greater than unity accounted for 83.1% of the total variability due to the variation of nine quality attributes considered for PC analysis, indicating that all quality attributes equally contribute to a grouping of the accessions in different clusters. Organoleptic cup quality attributes showed positive and significant correlations both at the genotypic and phenotypic levels, demonstrating the possibility of simultaneous improvement of the traits. Path coefficient analysis revealed that acidity, flavor, and body had a high positive direct effect on overall cup quality, implying that these traits can be used as indirect criteria to improve overall coffee quality. Therefore, it was concluded that there is considerable variation among the accessions, which need to be properly conserved for future improvement of the coffee quality. However, the variability observed for quality attributes must be further verified using biochemical and molecular analysis.

Keywords: accessions, Coffea arabica, cluster analysis, correlation, principal component

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Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple Kinect sensor

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Authors: Yolanda Indah Permatasari, Sudarsono Hardjosoekarto

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Public private partnership (PPP) scheme was considered as an alternative source of funding for infrastructure provision. However, the performance of PPP scheme and interest of private sector to participate in the provision of infrastructure was still practically low. This phenomenon motivates the research to reconstruct the form of collaborative governance at the policy level from the perspective of transaction cost of the PPP scheme. Soft-system methodology (SSM)-based action research was used as this research methodology. The result of this study concludes that the emergence of transaction cost sources at the policy level is caused by the absence of a law that governs infrastructure investment, especially the implementation of PPP scheme. This absence is causing the imbalance in risk allocation and risk mitigation between the public and private sector. Thus, this research recommended the formulation of infrastructure investment law that aims to minimize asymmetry information, to anticipate the principal-principal problems, and to provide legal basis that ensures risk certainty and guarantee fair risk allocation between public and private sector.

Keywords: public governance, public private partnership, soft system methodology, transaction cost

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Authors: Syed Afrozuddin Ahmed, Junaid Saghir Siddiqi, Sabah Quaiser

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Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan. In this study it has been investigated that spatial pattern of environment causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. The climatic or environmental structure data and the Dengue Fever (DF) data was processed by coding, editing, tabulating, recoding, restructuring in terms of re-tabulating was carried out, and finally applying different statistical methods, techniques, and procedures for the evaluation. Five climatic variables which we have studied are precipitation (P), Maximum temperature (Mx), Minimum temperature (Mn), Humidity (H) and Wind speed (W) collected from 1980-2012. The dengue cases in Karachi from 2010 to 2012 are reported on weekly basis. Principal component analysis is applied to explore the climatic variables and/or the climatic (structure) which may influence in the increase or decrease in the number of dengue fever cases in Karachi. PC1 for all the period is General atmospheric condition. PC2 for dengue period is contrast between precipitation and wind speed. PC3 is the weighted difference between maximum temperature and wind speed. PC4 for dengue period contrast between maximum and wind speed. Negative binomial and Poisson regression model are used to correlate the dengue fever incidence to climatic variable and principal component score. Relative humidity is estimated to positively influence on the chances of dengue occurrence by 1.71% times. Maximum temperature positively influence on the chances dengue occurrence by 19.48% times. Minimum temperature affects positively on the chances of dengue occurrence by 11.51% times. Wind speed is effecting negatively on the weekly occurrence of dengue fever by 7.41% times.

Keywords: principal component analysis, dengue fever, negative binomial regression model, poisson regression model

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Authors: Mohammed Hasan Salahat, Stave Wade

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This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modeling Language (UML), and an implementation pattern knows as ‘Naked Objects’. This framework have been used in action research projects that have involved the investigation and modeling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study ‘Information Retrieval System for Academic Research’ is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modeling. The framework is overviewed and justified as multi-methodology using Mingers Multi-Methodology ideas.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Jinen Daghrir, Anis Kricha, Karim Kalti

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The amount of incoming administrative documents is massive and manually processing these documents is a costly task especially on the timescale. In fact, this problem has led an important amount of research and development in the context of automatically extracting fields from administrative documents, in order to reduce the charges and to increase the citizen satisfaction in administrations. In this matter, we introduce an administrative document understanding system. Given a document in which a user has to select fields that have to be retrieved from a document class, a document model is automatically built. A document model is represented by an attributed relational graph (ARG) where nodes represent fields to extract, and edges represent the relation between them. Both of vertices and edges are attached with some feature vectors. When another document arrives to the system, the layout objects are extracted and an ARG is generated. The fields extraction is translated into a problem of matching two ARGs which relies mainly on the comparison of the spatial relationships between layout objects. Experimental results yield accuracy rates from 75% to 100% tested on eight document classes. Our proposed method has a good performance knowing that the document model is constructed using only one single document.

Keywords: administrative document understanding, logical labelling, logical layout analysis, fields extraction from administrative documents

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Authors: Khin Aye Myint, Mohd Rafii Yusop, Mohd Yusoff Abd Samad, Shairul Izan Ramlee, Mohd Din Amiruddin, Zulkifli Yaakub

Abstract:

The narrow base of genetic is the main obstacle of breeding and genetic improvement in oil palm industry. In order to broaden the genetic bases, the Malaysian Palm Oil Board has been extensively collected wild germplasm from its original area of 11 African countries which are Nigeria, Senegal, Gambia, Guinea, Sierra Leone, Ghana, Cameroon, Zaire, Angola, Madagascar, and Tanzania. The germplasm collections were established and maintained as a field gene bank in Malaysian Palm Oil Board (MPOB) Research Station in Kluang, Johor, Malaysia to conserve a wide range of oil palm genetic resources for genetic improvement of Malaysian oil palm industry. Therefore, assessing the performance and genetic diversity of the wild materials is very important for understanding the genetic structure of natural oil palm population and to explore genetic resources. Principal component analysis (PCA) and Cluster analysis are very efficient multivariate tools in the evaluation of genetic variation of germplasm and have been applied in many crops. In this study, eight populations of MPOB-Senegal oil palm germplasm were studied to explore the genetic variation pattern using PCA and cluster analysis. A total of 20 yield and yield component traits were used to analyze PCA and Ward’s clustering using SAS 9.4 version software. The first four principal components which have eigenvalue >1 accounted for 93% of total variation with the value of 44%, 19%, 18% and 12% respectively for each principal component. PC1 showed highest positive correlation with fresh fruit bunch (0.315), bunch number (0.321), oil yield (0.317), kernel yield (0.326), total economic product (0.324), and total oil (0.324) while PC 2 has the largest positive association with oil to wet mesocarp (0.397) and oil to fruit (0.458). The oil palm population were grouped into four distinct clusters based on 20 evaluated traits, this imply that high genetic variation existed in among the germplasm. Cluster 1 contains two populations which are SEN 12 and SEN 10, while cluster 2 has only one population of SEN 3. Cluster 3 consists of three populations which are SEN 4, SEN 6, and SEN 7 while SEN 2 and SEN 5 were grouped in cluster 4. Cluster 4 showed the highest mean value of fresh fruit bunch, bunch number, oil yield, kernel yield, total economic product, and total oil and Cluster 1 was characterized by high oil to wet mesocarp, and oil to fruit. The desired traits that have the largest positive correlation on extracted PCs could be utilized for the improvement of oil palm breeding program. The populations from different clusters with the highest cluster means could be used for hybridization. The information from this study can be utilized for effective conservation and selection of the MPOB-Senegal oil palm germplasm for the future breeding program.

Keywords: cluster analysis, genetic variability, germplasm, oil palm, principal component analysis

Procedia PDF Downloads 140