bluuebunny/crossref_metadata_2025 huggingface dataset:
Analyzing Spinal Shape Changes During Posture Training Using a Wearable Device
Authors: Stollenwerk Katharina , Müller Jonas , Hinkenjann André , Krüger Björn
Published: August 2019

Lower back pain is one of the most prevalent diseases in Western societies. A large percentage of European and American populations suffer from back pain at some point in their lives. One successful approach to address lower back pain is postural training, which can be supported by wearable devices, providing real-time feedback about the user’s posture. In this work, we analyze the changes in posture induced by postural training. To this end, we compare snapshots before and after training, as measured by the Gokhale SpineTracker™. Considering pairs of before and after snapshots in different positions (standing, sitting, and bending), we introduce a feature space, that allows for unsupervised clustering. We show that resulting clusters represent certain groups of postural changes, which are meaningful to professional posture trainers.
Adaptive Neuro-Fuzzy Fusion of Multi-Sensor Data for Monitoring a Pilot’s Workload Condition
Authors: Zhang Xia , Sun Youchao , Qiu Zhifan , Bao Junping , Zhang Yanjun
Published: August 2019

To realize an early warning of unbalanced workload in the aircraft cockpit, it is required to monitor the pilot’s real-time workload condition. For the purpose of building the mapping relationship from physiological and flight data to workload, a multi-source data fusion model is proposed based on a fuzzy neural network, mainly structured using a principal components extraction layer, fuzzification layer, fuzzy rules matching layer, and normalization layer. Aiming at the high coupling characteristic variables contributing to workload, principal component analysis reconstructs the feature data by reducing its dimension. Considering the uncertainty for a single variable to reflect overall workload, a fuzzy membership function and fuzzy control rules are defined to abstract the inference process. An error feedforward algorithm based on gradient descent is utilized for parameter learning. Convergence speed and accuracy can be adjusted by controlling the gradient descent rate and error tolerance threshold. Combined with takeoff and initial climbing tasks of a Boeing 737–800 aircraft, crucial performance indicators—including pitch angle, heading, and airspeed—as well as physiological indicators—including electrocardiogram (ECG), respiration, and eye movements—were featured. The mapping relationship between multi-source data and the comprehensive workload level synthesized using the NASA task load index was established. Experimental results revealed that the predicted workload corresponding to different flight phases and difficulty levels showed clear distinctions, thereby proving the validity of data fusion.
Agreement Analysis between Vive and Vicon Systems to Monitor Lumbar Postural Changes
Authors: van der Veen Susanne , Bordeleau Martine , Pidcoe Peter , France Christopher , Thomas James
Published: August 2019

Immersive virtual reality has recently developed into a readily available system that allows for full-body tracking. Can this affordable system be used for component tracking to advance or replace expensive kinematic systems for motion analysis in the clinic? The aim of this study was to assess the accuracy of position and orientation measures from Vive wireless body trackers when compared to Vicon optoelectronic tracked markers attached to (1) a robot simulating trunk flexion and rotation by repeatedly moving to know locations, and (2) healthy adults playing virtual reality games necessitating significant trunk displacements. The comparison of both systems showed component tracking with Vive trackers is accurate within 0.68 ± 0.32 cm translationally and 1.64 ± 0.18° rotationally when compared with a three-dimensional motion capture system. No significant differences between Vive trackers and Vicon systems were found suggesting the Vive wireless sensors can be used to accurately track joint motion for clinical and research data.
Towards Model-Free Tool Dynamic Identification and Calibration Using Multi-Layer Neural Network
Authors: Su Hang , Qi Wen , Hu Yingbai , Sandoval Juan , Zhang Longbin , Schmirander Yunus , Chen Guang , Aliverti Andrea , Knoll Alois , Ferrigno Giancarlo , De Momi Elena
Published: August 2019

In robot control with physical interaction, like robot-assisted surgery and bilateral teleoperation, the availability of reliable interaction force information has proved to be capable of increasing the control precision and of dealing with the surrounding complex environments. Usually, force sensors are mounted between the end effector of the robot manipulator and the tool for measuring the interaction forces on the tooltip. In this case, the force acquired from the force sensor includes not only the interaction force but also the gravity force of the tool. Hence the tool dynamic identification is required for accurate dynamic simulation and model-based control. Although model-based techniques have already been widely used in traditional robotic arms control, their accuracy is limited due to the lack of specific dynamic models. This work proposes a model-free technique for dynamic identification using multi-layer neural networks (MNN). It utilizes two types of MNN architectures based on both feed-forward networks (FF-MNN) and cascade-forward networks (CF-MNN) to model the tool dynamics. Compared with the model-based technique, i.e., curve fitting (CF), the accuracy of the tool identification is improved. After the identification and calibration, a further demonstration of bilateral teleoperation is presented using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrate the promising performance of the model-free tool identification technique using MNN, improving the results provided by model-based methods.
How Significant Are Differences Obtained by Neglecting Correlations When Testing for Deformation: A Real Case Study Using Bootstrapping with Terrestrial Laser Scanner Observations Approximated by B-Spline Surfaces
Authors: Kermarrec Gaël , Paffenholz Jens-André , Alkhatib Hamza
Published: August 2019

B-spline surfaces possess attractive properties such as a high degree of continuity or the local support of their basis functions. One of the major applications of B-spline surfaces in engineering geodesy is the least-square (LS) fitting of surfaces from, e.g., 3D point clouds obtained from terrestrial laser scanners (TLS). Such mathematical approximations allow one to test rigorously with a given significance level the deformation magnitude between point clouds taken at different epochs. Indeed, statistical tests cannot be applied when point clouds are processed in commonly used software such as CloudCompare, which restrict the analysis of deformation to simple deformation maps based on distance computation. For a trustworthy test decision and a resulting risk management, the stochastic model of the underlying observations needs, however, to be optimally specified. Since B-spline surface approximations necessitate Cartesian coordinates of the TLS observations, the diagonal variance covariance matrix (VCM) of the raw TLS measurements has to be transformed by means of the error propagation law. Unfortunately, this procedure induces mathematical correlations, which can strongly affect the chosen test statistics to analyse deformation, if neglected. This may lead potentially to rejecting wrongly the null hypothesis of no-deformation, with risky and expensive consequences. In this contribution, we propose to investigate the impact of mathematical correlations on test statistics, using real TLS observations from a bridge under load. As besides TLS, a highly precise laser tracker (LT) was used, the significance of the difference of the test statistics when the stochastic model is misspecified can be assessed. However, the underlying test distribution is hardly tractable so that only an adapted bootstrapping allows the computation of trustworthy p-values. Consecutively, the extent to which heteroscedasticity and mathematical correlations can be neglected or simplified without impacting the test decision is shown in a rigorous way, paving the way for a simplification based on the intensity model.
The Relationship between Corporate Sustainability Disclosure and Firm Financial Performance in Johannesburg Stock Exchange (JSE) Listed Mining Companies
Authors: Wasara Tafadzwa Mark , Ganda Fortune
Published: August 2019

Whether corporate sustainability disclosure (CSD) affects profitability remains indistinct to many firms. This paper examines the relationship between corporate sustainability disclosure and return on investment. The sample of this study consisted of ten Johannesburg Stock Exchange (JSE)-listed mining companies, and the data was extracted from sustainability reports for a period of five years from 2010 to 2014. In this regard, data collection was undertaken by the adoption of a content analysis approach. A multi-regression analysis was used to analyze the relationship between environmental disclosure and return on investment. The same statistical mechanism was employed to determine the association involving social disclosure and return on investment. Results show that there is a negative relationship between environmental disclosure and return on investment. On the other hand, the research reveals that there is also a positive association between social disclosure and return on investment. This implies that an increase in corporate reporting of social issues results in heightened financial performance through an increase in return on investment. This study recommends the adoption of corporate social disclosure as it will encourage firms to be socially responsible, while also generating financial benefits. Further studies can be conducted about the change from voluntary corporate social disclosure to mandatory disclosure.
Artificial Intelligence Based Commercial Risk Management Framework for SMEs
Authors: Žigienė Gerda , Rybakovas Egidijus , Alzbutas Robertas
Published: August 2019

Risk management in commercial processes is among the most important procedures affecting the competitiveness of small and medium-sized enterprises (SMEs), their innovativeness and potential contribution to global sustainable development goals (SDGs). The ecosystem of commercial processes is the prerequisite to manage risk faced by SMEs. Commercial risk assessment and management using elements of artificial intelligence, big data, and machine learning technologies could be developed and maintained as external services for a group of SMEs allowing to share costs and benefits. This paper aims to provide a conceptual framework of commercial risk assessment and management solution based on elements of artificial intelligence. This conceptualization is done on the background of scientific literature, policy documents, and risk management standards. Main building blocks of the framework in terms of commercial risk categories, data sources and workflow phases are presented in the article. Business companies, state policy, and academic research focused recommendations on the further development of the framework and its implementation are elaborated.
Stochastic Unit Commitment and Optimal Power Trading Incorporating PV Uncertainty
Authors: Sediqi Mohammad Masih , Lotfy Mohammed Elsayed , Ibrahimi Abdul Matin , Senjyu Tomonobu , K Narayanan.
Published: August 2019

This paper focuses on the optimal unit commitment (UC) scheme along with optimal power trading for the Northeast Power System (NEPS) of Afghanistan with a penetration of 230 MW of PV power energy. The NEPS is the biggest power system of Afghanistan fed from three main sources; 1. Afghanistan’s own power generation units (three thermal units and three hydro units); 2. imported power from Tajikistan; 3. imported power from Uzbekistan. PV power forecasting fluctuations have been handled by means of 50 scenarios generated by Latin-hypercube sampling (LHS) after getting the point solar radiation forecast through the neural network (NN) toolbox. To carry out the analysis, we consider three deterministic UC and two stochastic UC cases with a two-stage programming model that indicates the day-ahead UC as the first stage and the intra-day operation of the system as the second stage. A binary-real genetic algorithm is coded in MATLAB software to optimize the proposed cases in terms of thermal units’ operation costs, import power tariffs, as well as from the perspective of the system reliability risks expressed as the reserve and load not served costs. The results indicate that in the deterministic UC models, the risk of reserve and load curtailment does exist. The stochastic UC approaches including the optimal power trading are superior to the deterministic ones. Moreover, the scheduled UC costs and reserves are different from the actual ones.
Impact of Corporate Environmental Responsibility on Investment Efficiency: The Moderating Roles of the Institutional Environment and Consumer Environmental Awareness
Authors: Zeng Shihong , Qin Yujia , Zeng Guowang
Published: August 2019

The increasingly serious destruction of the natural environment represents a great threat to the sustainable development of human beings and the earth. Under pressure from the government and public opinion, companies must assume environmental responsibility; however, there is no conclusion on whether corporate environmental responsibility is beneficial to companies. From the perspective of investment efficiency, this paper collects panel data from Chinese listed companies from 2011 to 2016 to discuss the impact of corporate environmental responsibility on investment efficiency and the moderating role of the institutional environment and consumer environmental awareness. The results show that corporate environmental responsibility can significantly positively affect investment efficiency, but this effect is not a short-term effect; it needs time to play a role. Second, in regions with a good institutional environment, corporate environmental responsibility has a more significant impact on improving investment efficiency. Finally, with the improvement of consumer environmental awareness, companies that assume environmental responsibility can address underinvestment. The research in this paper supports stakeholder theory, indicating that corporate environmental responsibility is not “selfless dedication”. In addition, the research results of this paper are robust and not subject to endogenous influences.
Extracurricular Activities in Higher Education and the Promotion of Reflective Learning for Sustainability
Authors: Díaz-Iso Ariane , Eizaguirre Almudena , García-Olalla Ana
Published: August 2019

The objective of higher education institutions is to integrate reflective learning that contributes to the development of a greater awareness among individuals of the importance of facing the 21st century’s sustainability challenges. This paper analyzes the impact of an extracurricular volunteer activity in Tangier, Morocco in the development of student reflection at a Spanish university. To this end, two objectives were proposed: (1) to explore the students’ primary reflections of the experience, and (2) analyze the students’ perceptions of the importance of participating in the experience in order to develop reflective learning. In the study, in-depth interviews were conducted with 23 students who participated in the volunteer activity. Data analysis was carried out using Iramuteq software to conduct a descending hierarchical classification (DHC), and MAXQDA software to conduct a constant comparison analysis. This research highlights the value of voluntary extracurricular activities in the development of reflections that guide change in the beliefs, attitudes, and daily behaviors of students that ultimately result in sustainability. Due to this, not only is it considered essential that students participate in social projects, but also that they undertake these projects with peers and instructors who can create environments of support and trust.
RETRACTED: Spatial–Temporal Characteristics and Determinants of Digital Divide in China: A Multivariate Spatial Analysis
Authors: Song Zhouying , Song Tao , Yang Yu , Wang Zhenbo
Published: August 2019

The digital divide has loomed as a sustainable development issue for over two decades and there has been much research in terms of efforts to measure the digital divide from different dimensions and scales. Drawing on spatial agglomeration analysis and multiple linear regression, this paper aims to reveal the spatiotemporal pattern of the prefectural digital divide in China and its determinants. The results show that there is a significant prefectural digital divide in China that is characterized by a decline of ICT development index (IDI) values from the east to the west as well as from core cities to more peripheral ones. Cities with high IDI values are mainly concentrated in large metropolitan areas in eastern China, whereas cities with low values tend to concentrate in poverty stricken regions in central and western China. However, the digital divide has been characterized by a reduction from 2001 to 2015. The results also show that both economic and educational factors have significant influences on the prefectural digital divide in China. During the early stages, the percentage of university students, urban residential income, and the urbanization rate were key factors. However, after 2010, the adult literacy rate and rural residential income determined the digital divide.
Opportunities for Slow Tourism in Madeira
Authors: Valls Josep-Francesc , Mota Luís , Vieira Sara Cristina Freitas , Santos Rossana
Published: August 2019

The slow tourism movement is gaining popularity as more destinations focus on the local environment and heritage experience. The approach to slow tourism usually occurs either when traditional destinations exhaust their life cycle with an evident reduction in sustainability, or when newly emerging destinations decide to develop in this way. The case of Madeira is different; the island has several decades of tourism development without excessive pressure or overcrowding, and in planning for the future it wants to sustain these conditions. Seeking to understand Madeira’s perception of the development model, we surveyed entrepreneurs in Madeira’s lodging, restaurant and bar, shopping, transportation, intermediation, and tourist activity industries, as well as its public sector. Even without having encountered the popularized the ideas of slow tourism, Madeira’s tourism entrepreneurs show significant alignment with the values of quieter tourism. In contrast to its mature counterparts (i.e., Europe’s other popular sun and beach destinations), for Madeira it is not a question of destroying or rehabilitating, but rather of continuing sustainable development processes. Our results suggest that although slow tourism is typically a reaction to a very advanced phase of the life cycle, it can be the result of an endogenous impulse, as is true for Madeira.
College Students’ Shared Bicycle Use Behavior Based on the NL Model and Factor Analysis
Authors: Ma Shuhong , Zhou Yechao , Yu Zhoulin , Zhang Yan
Published: August 2019

The rise and rapid development of bicycle sharing brings great convenience to residents’ travel and transfer, and also has a profound impact on the travel structure of cities. As college students make up a major share of shared bicycle users, it is necessary to analyze the factors that influence their travel mode and riding frequency choice and to explore how these factors affect their riding behavior. To analyze the bicycle riding characteristics of college students, this paper processes many factors with unknown correlations by using a factor analysis method based on revealed preference (RP) questionnaire data. Then, taking the significant common factors as explanatory variables, a two-layer nested logit (NL) model combining riding frequency and travel mode is established to study college students’ riding behavior. The results suggest that the comprehensive hit rate of the upper and lower levels of the model (riding frequency and travel mode) are, respectively, 76.8% and 83.7%, and the two-layer NL model is applicable. It is also shown that environmental factors (“cheap,” “mixed traffic,” “signal lights at intersection,” and so on) have a significant impact on the choice of travel mode and riding frequency. Also, improving the level of bicycle service can increase the shift from walking to riding. Such findings are meaningful for policy-makers, planners, and others in formulating operational management strategies and policies.
Experimental Study on a Novel Dry Connection for a Precast Concrete Beam-To-Column Joint
Authors: Zhong Yachao , Xiong Feng , Chen Jiang , Deng Ai , Chen Wen , Zhu Xulong
Published: August 2019

At present, precast buildings have become the focus of the building industrialization, and the precast concrete frame structure has been widely used in the construction industry. On this background, a novel precast concrete frame with a bolt connection joint was proposed in this paper. The novel connections include connection steel plates, bolts and rubber layers. To investigate the seismic performance of the precast structure, two full-scale, precast, cruciform, reinforced concrete specimens, and a monolithic counterpart, are tested under reversed cyclic loading. For the precast specimens, two different thickness rubber layers are applied in the connection region, respectively. Seismic behavior was evaluated based on failure mode, hysteretic behavior, stiffness degeneration, ductility and energy dissipation. The results indicated that precast specimens had almost the same ultimate bearing capacity as the cast-in-place ones, and the failure mode is also the same. The precast specimens satisfied the strong column-weak beam design concept. Additionally, the initial stiffness is obviously decreased by adding rubber washers at the joint region, showing a semi-rigid characteristic. At the end of this paper, an equivalent stiffness computation method of the precast joint is discussed.
Cointegration and Causality Analysis of Dynamic Linkage between Industrial Energy Consumption and Economic Growth in Pakistan
Authors: Chandio Abbas Ali , Rauf Abdul , Jiang Yuansheng , Ozturk Ilhan , Ahmad Fayyaz
Published: August 2019

Energy consumption is a crucial factor to promote industrial sector contribution in an economy for its economic progression. Indeed, Pakistan is an emerging country, but recently adjoining with a very severe deficit of electricity sources. Hence, the industry value added growth leading to economic progression is also fronting inevitable challenges to promote the industry growth. The main objective of the study is to investigate the linkages between industrial sector oil, gas and electricity consumption, and renewable energy consumption with economic development in Pakistan. The findings display evidence of cointegration and a long-run relationship between the consumption of industrial energy and economic growth in Pakistan. The results showed that industrial electricity consumption and industrial gas consumption have a positive and statistically significant impact on economic growth both in the long run and the short run in Pakistan. Industrial oil consumption negatively impacts economic growth in the long run, but positively and statistically significantly impacts economic growth in the short run in Pakistan. Moreover, indications through the vector error correction model (VECM) model confirmed bi-directional relationships of industrial sector oil consumption and economic growth in Pakistan. Furthermore, the uni-directional nexus instituted between economic growth to industrial electricity consumption, industrial gas consumption to industrial electricity consumption, and industrial oil consumption to industrial electricity consumption. The findings uncovered solid interconnections among the studied variables and suggested that the Pakistani government should build a robust policy to diminish the oil, gas, and fossil fuels consumption for electricity production, as a replacement to depend on solar, hydro, wind, and biomass energy sources in Pakistan. Consequently, the government should promote more gas concentrated projects, as these will alleviate the contests of gas dearth and provide it to the industry at cheap prices with ease.
Assessing Urban Areas’ Vulnerability to Flood Disaster Based on Text Data: A Case Study in Zhengzhou City
Authors: Wu Zening , Shen Yanxia , Wang Huiliang
Published: August 2019

Confronting the frequent flood disasters triggered by torrential downpour, the vulnerability of urban rainstorm flood disasters was analyzed with one highly popular area of research in mind: big data. Web crawler technology was used to extract text information related to floods from Internet and popular social media platforms. Combining these text data with traditional statistical data, a flood disaster vulnerability assessment model based on Analytic Hierarchy Process (AHP) was established to evaluate rainstorm and flood disaster vulnerability, and the spatial distribution characteristics of vulnerability to pluvial flooding were analyzed based on Geographic Information System (GIS). The established model was applied in Zhengzhou, a city that often suffers from heavy rainstorms. The results show that the areas located near downtown Zhengzhou were more vulnerable to rainstorm and flooding than others, and most of the city could be at moderate and high vulnerability. Finally, the waterlogging spots extracted from various sources were used to evaluate the performance of the proposed model. The results show that most of waterlogging spots were located in very-high and high risk zones, while less waterlogging spots were found in districts with low vulnerability, which demonstrates the discriminative power of the established model based on big data sources. This study overcomes limited data in flood disaster vulnerability assessment methods and provides a basis for flood control and management in cities.
Evaluation of Rolling Bearing Performance Degradation Using Wavelet Packet Energy Entropy and RBF Neural Network
Authors: Zhou Jianmin , Wang Faling , Zhang Chenchen , Zhang Long , Li Peng
Published: August 2019

Rolling bearings are the most important parts in rotating machinery, and one of the most vulnerable parts to failure. The rolling bearing is a cyclic symmetrical structure that is stable under normal operating conditions. However, when the rolling bearing fails, its symmetry is destroyed, resulting in unstable performance and causing major accidents. If the performance of rolling bearings can be monitored and evaluated in real time, maintenance strategies can be implemented promptly. In this paper, by using wavelet packet energy entropy (WPEE), the early fault-free features of bearing and the failure samples of similar bearings are decomposed firstly, and the energy value is extracted as the original feature, simultaneously. Secondly, a radial basis function (RBF) neural network model is established by using early fault-free features and similar bearing failure characteristics. The bearing full-life data characteristics of the extracted features are added into the RBF model in an iterative manner to obtain performance degradation Indicator. Boxplot was introduced as an adaptive threshold method to determine the failure threshold. Finally, the results are verified by empirical mode decomposition and Hilbert envelope demodulation. A bearing accelerated life experiment is performed to validate the feasibility and validity of the proposed method. The experimental results show that the method can diagnose early fault points in time and evaluate the degree of bearing degradation, which is of great significance for industrial practical applications.
Composite Quantile Regression for Varying Coefficient Models with Response Data Missing at Random
Authors: Luo Shuanghua , Zhang Cheng-yi , Wang Meihua
Published: August 2019

Composite quantile regression (CQR) estimation and inference are studied for varying coefficient models with response data missing at random. Three estimators including the weighted local linear CQR (WLLCQR) estimator, the nonparametric WLLCQR (NWLLCQR) estimator, and the imputed WLLCQR (IWLLCQR) estimator are proposed for unknown coefficient functions. Under some mild conditions, the proposed estimators are asymptotic normal. Simulation studies demonstrate that the unknown coefficient estimators with IWLLCQR are superior to the other two with WLLCQR and NWLLCQR. Moreover, bootstrap test procedures based on the IWLLCQR fittings is developed to test whether the coefficient functions are actually varying. Finally, a type of investigated real-life data is analyzed to illustrated the applications of the proposed method.
Measles Elimination: Identifying Susceptible Sub-Populations to Tailor Immunization Strategies
Authors: Kreidl Peter , Ammerer David , Würzner Reinhard , Luckner Hornischer Anita , von Laer Dorothee , Borena Wegene
Published: August 2019

Measles elimination has been identified as a public health priority in Europe for a long time but has not yet been achieved. The World Health Organization (WHO) recommends identification of susceptible sub-populations to target supplementary immunization activities. We used three different sources of information: retrospective samples investigated for measles IgG between 1997 and 2016, vaccine coverage data from the existing electronic registry for birth cohorts 2015 to 1999, and surveillance data from 2009 until 20 July 2019. We calculated susceptibility by birth cohort using seroprevalence data, adjusting vaccine coverage data with reported effectiveness (93% for the first and 97% for the second dose, respectively), and compared it with measles incidence data, aggregated by birth cohorts and districts. Susceptibility levels for persons 10–41 years (birth cohorts 2007–1976) were 10.4% and thus far above the recommended values of WHO (5%). Older birth cohorts were sufficiently protected. Districts with the highest susceptibility estimates corresponded with districts with the highest incidence rates. Birth cohorts with susceptibility levels > 10% showed a 4.7 increased relative risk of having had more than one measles case. We conclude that retrospective serosurveys are a cheap and useful approach in identifying susceptible sub-populations, especially for older birth cohorts whose coverage data remain scarce.
The Influence of a Water Absorbing Geocomposite on Soil Water Retention and Soil Matric Potential
Authors: Śpitalniak Michał , Lejcuś Krzysztof , Dąbrowska Jolanta , Garlikowski Daniel , Bogacz Adam
Published: August 2019

Climate change induces droughts that are becoming more intensive and more frequent than ever before. Most of the available forecast tools predict a further significant increase in the risk of drought, which indicates the need to prepare solutions to mitigate its effects. Growing water scarcity is now one of the world’s leading challenges. In agriculture and environmental engineering, in order to increase soil water retention, soil additives are used. In this study, the influence of a newly developed water absorbing geocomposite (WAG) on soil water retention and soil matric potential was analyzed. WAG is a special element made from geotextile which is wrapped around a synthetic skeleton with a superabsorbent polymer placed inside. To describe WAG’s influence on soil water retention and soil matric potential, coarse sand, loamy sand, and sandy loam soils were used. WAG in the form of a mat was used in the study as a treatment. Three kinds of samples were prepared for every soil type. Control samples and samples with WAG treatment placed at depths of 10 cm and 20 cm were examined in a test container of 105 × 70 × 50 cm dimensions. The samples had been watered and drained, and afterwards, the soil surface was heated by lamps of 1100 W total power constantly for 72 h. Soil matric potential was measured by Irrometer field tensiometers at three depths. Soil moisture content was recorded at six depths: of 5, 9, 15, 19, 25, and 30 cm under the top of the soil surface with time-domain reflectometry (TDR) measurement devices. The values of soil moisture content and soil matric potential were collected in one-minute steps, and analyzed in 24-h-long time steps: 24, 48, and 72 h. The samples with the WAG treatment lost more water than the control samples. Similarly, lower soil matric potential was noted in the samples with the WAG than in the control samples. However, after taking into account the water retained in the WAG, it appeared that the samples with the WAG had more water easily available for plants than the control samples. It was found that the mechanism of a capillary barrier affected higher water loss from soil layers above those where the WAG had been placed. The obtained results of water loss depend on the soil type used in the profile.
Large Scale Flood Hazard Analysis by Including Defence Failures on the Dutch River System
Authors: Curran Alex , de Bruijn Karin , Klerk Wouter , Kok Matthijs
Published: August 2019

To make informed flood risk management (FRM) decisions in large protected river systems, flood risk and hazard analyses should include the potential for dike breaching. ‘Load interdependency’ analyses attempt to include the system-wide effects of dike breaching while accounting for the uncertainty of both river loads and dike fragility. The intensive stochastic computation required for these analyses often precludes the use of complex hydraulic models, but simpler models may miss spatial inundation interactions such as flows that ‘cascade’ between compartmentalised regions and overland flows that ‘shortcut’ between river branches. The potential for these interactions in the Netherlands has previously been identified, and so a schematisation of the Dutch floodplain and protection system is here developed for use in a load interdependency analysis. The approach allows for the spatial distribution of hazard to be quantified under various scenarios and return periods. The results demonstrate the importance of including spatial inundation interactions on hazard estimation at three specific locations, and for the system in general. The modelling approach can be used at a local scale to focus flood-risk analysis and management on the relevant causes of inundation, and at a system-wide scale to estimate the overall impact of large-scale measures.
Restructuring a Water Distribution Network through the Reactivation of Decommissioned Water Tanks
Authors: Viccione Giacomo , Ingenito Laura , Evangelista Stefania , Cuozzo Carmine
Published: August 2019

Water resource management is a topic of great environmental and social relevance, since water must be preserved and managed to avoid waste, providing high quality service at fair tariffs for the consumer, as imposed by the European Water Directive (2000/CE). In the rehabilitation of a water distribution network, it may be suitable to recover decommissioned water tanks, if any, rather than afford high construction costs to build new ones. In this case, the assessment of the residual service life of these concrete structures affected by steel bar corrosion is the premise for the design of new pipeline routes, connecting them. For this aim, rather than carrying tests that can accurately determine mechanical properties of the dismissed water tanks, it is possible to empirically estimate their level of degradation. Their conditions infer on the expected life of the restructured water distribution network. However, they allow the aqueduct to be used for its technical duration, assumed to be equal to the decommissioned water tanks residual service life in the case they do not require maintenance. Here, a simplified model for the assessment of the residual service life of decommissioned water tanks is first proposed and then applied to a case study, consisting of a part of the water network managed by “Ausino S.p.A. Servizi Idrici Integrati”, Cava de’ Tirreni, Italy. Once the service life is assessed, the QEPANET plugin is used in QGIS to speed up the design of the new pipeline routes in the georeferenced space, thus overcoming the limits offered by the classic EPANET solver.
ANALISIS PERFORMANSI MAHASISWA DENGAN MENGGUNAKAN METODE FMECA DI PROGRAM STUDI TEKNIK INDUSTRI UNIVERSITAS KOMPUTER INDONESIA
Authors: Anthara Made Aryantha
Published: August 2019

Salah satu komponen penting dalam sebuah system pendidikan adalah mahasiswa yang sedang mengikuti proses perkuliahan. Salah satu indicator keberhasilan mahasiswa dapat dilihat dari nilai Indeks Prestasi (IP) yang diperoleh pada tiap semester. Besar kecilnya nilai IP tergantung dari tingkat kelulusan sebuah mata kuliah. Banyak yang bisa menyebabkan mahasiswa gagal dalam sebuah mata kuliah, sehingga perlu dicari akar permasalahan utama yang kemudian dapat menentukan solusi perbaikan terhadap kondisi tersebut.

Dalam penelitian ini, objek yang dijadikan bahan penelitian adalah system perkuliahan mahasiswa di Program Studi Teknik Industri dengan mengambil studi kasus khusus angkatan 2014 yang saat ini menjadi angkatan yang sudah masuk ke dalam tahun akhir perkuliahan. Dengan melihat kartu hasil studi dari tiap mahasiswa 2014 dari mulai semester awal, maka diharapkan dapat diketahui jenis mata kuliah yang tingkat ketidak lulusannya besar. Kemudian akan ditentukan prioritas perbaikan yang dapat dilakukan oleh mahasiswa dan program studi untuk dapat mengatasi permasalahan ini.

Permasalahan yang sering terjadi adalah mahasiswa sering mengalami ketidak lulusan terhadap beberapa mata kuliah yang diajarkan. Hal ini bisa menghambat kegiatan akademik yang ada di program studi, karena diantaranya harus mengatur jumlah kelas untuk mahasiswa yang mengulang. Selain itu, semakin besar persentasi mahasiswa yang tidak lulus, maka akan menghambat mahasiswa tersebut untuk dapat lulus tepat pada waktunya.

Hasil dari penelitian menyatakan bahawa terdapat dua mata kuliah yang dianggap paling sering mengalami ketidaklulusan oleh mahasiswa angkatan 2014 yaitu mata kuliah Pengendalian dan Penjaminan Mutu dan Pemodelan Sistem.Dalam penelitian ini telah dibuatkan worksheet FMECA yang memberikan informasi penyebab kegagalan mahasiswa dalam sebuah perkuliahan serta akan ditentukan bagaimana solusi perbaikannya sehingga mahasiswa dapat lulus tepat pada waktunya dan kegiatan akademik di Program Studi Teknik Industri di Universitas Komputer Indonesia dapat berjalan baik.
PERMODELAN SIMULASI UNTUK PERBAIKAN TATA LETAK PADA PABRIK SPUN PILE DI PT WASKITA BETON PRECAST TBK. PLANT SUBANG MENGGUNAKAN PRO-MODEL
Authors: Santosa Alam , Rachim Fathur Rahman
Published: August 2019

Tata letak pada lantai produksi pembuatan produk spun pile di PT Waskita sudah diatur sedemikian rupa, namun masih ada transportasi bolak balik. Transportasi bolak balik tersebut terjadi diantara departemen setting joint plate dan setting moulding, sehingga menimbulkan biaya transportasi yang besar dan pada area penyimpanan, bahan baku terbagi dalam beberapa departemen. Pembangunan tata letak dengan metode simulasi dapat membantu dalam memilih alternatif tata letak yang dirancang karena dapat menghemat waktu dan biaya. Eksperimen dilakukan sesuai dengan alternatif Activity Relationship Diagram (ARD). ARD dibuat terdiri dari 11 ARD yang diusulkan untuk dilakukan ekperimen perhitungan ongkos material handling menggunakan Pro-Model. ARD yang terpilih adalah ARD alternatif ke sepuluh, karena mamiliki ongkos yang terkecil. Pada ARD alternatif kesepuluh ini, model yang dibuat terdiri dari 15 lokasi, 7entitas, 7 path network yang mengarahkan alat angkut, 7 resource serta 4 titik kedatangan bahan baku dan bahan baku tambahan. Pada model usulan ini terdiri dari 16 proses mulai dari pengolahan bahan baku hingga produk jadi. Hasil produksi selama satu hari kerja sesuai dengan model usulan adalah 81 produk spun pile. Sehingga total ongkos material handling yang digunakan dalam satu hari produksi adalah sebesar Rp. 52.904.297.79 dengan jam kerja selama 20 jam. Maka ongkos material handling yang dikeluarkan untuk membuat 1 buah produk spun pile sebesar Rp. 653.139.47. Perbandingan antara model awal dan model usulan dilakukan dengan tujuan agar mengetahui ongkos material handling terkecil. Pada model awal ongkos material handling yang dibutuhkan dalam membuat satu buah produk adalah sebesar Rp. 730.159.28. Sementara itu produk yang dihasilkan pada model awal adalah 61 produk.
PENGARUH BEBAN KERJA PRAKTIKUM DAN MOTIVASI TERHADAP KINERJA MAHASISWA DALAM BERKOMPETISI PADA NILAI AKADEMIK
Authors: Andriana Iyan , Rinaldy Aldi Muhammad
Published: August 2019

Penelitian ini bertujuan untuk menjelaskan pengaruh beban kerja praktikum dan motivasi terhadap kinerja mahasiswa. Fenomena yang terjadi saat ini praktikum memiliki beban satu sks namun setara dengan tiga jam mata kuliah, berbeda dengan mata kuliah seperti pada biasanya. Metode analisis jalur dapat menjelaskan seberapa besar kinerja mahasiswa dapat dipengaruhi oleh beban kerja praktikum dan motivasi. Analisis jalur adalah teknik pengembangan dari regresi linear berganda yang digunakan untuk menguji variabel objek penelitian pada setiap jalur. Input pada penelitian ini adalah beban kerja praktikum memiliki hubungan positif dan signifikan dengan motivasi sebesar 0.32. Penelitian ini memiliki tiga hasil, pertama, ada pengaruh beban kerja praktikum dan motivasi terhadap kinerja mahasiswa. Kedua, ada pengaruh antara beban kerja praktikum dengan kinerja mahasiswa. Ketiga, ada pengaruh motivasi terhadap kinerja mahasiswa. Masing-masing nilai secara berurutan adalah 50.03%, 16.98%, dan 33.05%. Berdasarkan hasil dan penggunaan tingkat signifikansi 5% menjelaskan bahwa semakin besar jumlah dari beban kerja praktikum, semakin mempengaruhi motivasi mahasiswa dan sebaliknya, penelitian ini menegaskan bahwa beban kerja praktikum dan motivasi memiliki efek signifikan pada kinerja mahasiswa.
ANALISIS EFEKTIVITAS MESIN INJECTION MOLDING DI BAGIAN PRODUKSI PT. DIAN MEGAH INDO PERKASA MENGGUNAKAN METODE OVERALL EQUIPMENT EFFECTIVENESS DAN FAULT TREE ANALYSIS
Authors: Sianturi Gabriel , Alatas Haidar
Published: August 2019

Salah satu faktor terpenting dalam proses produksi adalah kinerja mesin. Mesin merupakan alat utama dalam pembuatan produk. PT Dian Megah Indo Perkasa merupakan perusahaan yang bergerak dibidang industry plastik dan terletak di Jl. Abdul Halim No. 30 Cimahi Badung, Jawa Barat. PT Dian Megah Indo Perkasa memilik 28 mesin injection molding, apabila salah satu mesin mengalami kerusakan ataupun penurunan performasi maka target produksi tidak akan tercapai.

 

Metode overall equipment effectiveness merupakan metode yang digunakan untuk menghitung efektivitas suatu mesin, dimana avalaibility, performance dan quality menjadi komponen terpenting dalam metode ini. Selain itu untuk dapat melihat nilai kerugian yang dialami oleh perusahaan maka diperlukanlah perhitungan metode Six Big Losses. Selanjutnya nilai efektivitas dan nilai Six Big Losses tersebut akan dianalisis menggunakan metode Fault Tree Analysis.

 

Mesin injection molding merupakan mesin yang memproduksi produk dari plastik, namun mesin ini belum sepenuhnya bekerja secara efektif. Hal ini dapat diketahui dari rendahnya nilai overall equipment effectiveness (OEE) yang telah dihitung yaitu sebesar 70,83% untuk periode Januari 2018, 74,25% untuk periode Februari 2018 dan 78,66% untuk periode Maret 2018. Nilai ini masih jauh dari target nilai ideal OEE yang telah ditetapkan oleh Seiichi Nakajima yaitu diatas 85%. Akar penyebab dari rendahnya nilai OEE tersebut adalah karena tingginya nilai six big losses yang telah dihitung.

 

Faktor yang menyebabkan rendahnya nilai efektivitas dan tingginya nilai Six Big Losses diantara lain yaitu breakdown pada mesin, penurunan kecepatan produksi, gangguan pada molding dan masih terdapat produk-produk yang tidak sesuai standar yang telah ditetapkan. Berdasarkan hasil pengolahan dan analisis yang telah dilakukan maka terdapat beberapa perbaikan yang dibutuhkan PT Dian Megah Indo Perkasa. Usulan perbaikan yang direkomendasikan meliputi eliminasi six big losses, pemberian seminar pelatihan pada seluruh operator mesin injection molding dan pembuatan standar operasional prosedur (SOP) guna meningkatkan nilai overall equipment effectiveness (OEE)
NEW EDUCATIONAL PARADIGMA AND STATE STANDARDS MUSIC EDUCATION IN ELEMENTARY SCHOOL
Authors: Popova Tsvetanka , Kroteva Nikolina
Published: August 2019

The report examines the new state educational standards (DSS) as regards the content of music curricula that were imposed by the Pre-school and School Education Act approved by the Ministry of Education and Science which entered into force on 01.08.2016. One of the main reasons for the creation of this law was the need for an adequate and adequate educational environment in which to promote the individual development of each person using attractive forms of training. The adopted DSS provides for the acquisition of different general and specific competences that are expected as a result of the music education at each educational level. After the analysis of the content of the music curriculum at an early stage, it is possible to ascertain their suitability for the new positive ideas and trends in the musical education process. Musical activities that construct the unit of study are tailored to the pupils' age skills to perceive music and their accumulated listening experience. The pre-set variety of textbooks with different author teams required a more detailed review. The new methodology for the presentation of elements of musical expression is in line with state educational standards. Noting literacy and the absorption of elements of musical expression have been set too early in first grade textbooks, but it is most widely used in music education in the third grade. It highlights the great thematic wealth associated with putting the foundations in the literacy and musical script. The key points are the concepts: pen, note key, notes, tonal names, pauses, size, tact, stroke, and so on. The expected key learning outcomes of the pupils' preparation are key competencies. We are pleased to note that the information provided in the curriculum is presented in an attractive way. Various visual aids are available in various variants of music textbooks: interesting, entertaining and accessible to children. The musical education process is based on the conditions for a more effective development of musical abilities as an effective force for emotional communication with music and the realization of musical activities. In this process a special place is given to the role of the teacher, who will guide his students in the right direction and unobtrusively enable them to be the creators of modern times.