Search results for: input mode

Authors: B.M. Balekwa, D.V.V. Kallon, D.J. Fourie

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Modal analysis is applied to establish the dynamic difference between vibration response of the rails supported on High Density Polyethylene (HDPE) and Hytrel/6358 rail pads. The experiment was conducted to obtain the results in the form of Frequency Response Functions (FRFs) in the vertical and lateral directions. Three antiresonance modes are seen in the vertical direction; one occurs at about 150 Hz when the rail resting on the Hytrel/6358 pad experiences a force mid-span. For the rail resting on this type of rail pad, no antiresonance occurs when the force is applied on the point of the rail that is resting on the pad and directly on top of a sleeper. The two antiresonance modes occur in a frequency range of 250 – 300 Hz in the vertical direction for the rail resting on HDPE pads. At resonance, the rail vibrates with a higher amplitude, but at antiresonance, the rail transmits vibration downwards to the sleepers. When the rail is at antiresonance, the stiffness of the rail pads play a vital role in terms of damping the vertical vibration to protect the sleepers. From the FRFs it is understood that the Hytrel/6358 rail pads perform better than the HDPE in terms of vertical response, given that at a lower frequency range of 0 – 300 Hz only one antiresonance mode was identified for vertical vibration of the rail supported on Hytrel/6358. This means the rail is at antiresonance only once within this frequency range and this is the only time when vibration is transmitted downwards.

Keywords: accelerance, FRF, rail corrugation, rail pad

Procedia PDF Downloads 181

Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs

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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.

Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance

Procedia PDF Downloads 114

Authors: Anastasia Stamatiou, Markus Odermatt, Dominic Leemann, Ludger J. Fischer, Joerg Worlitschek

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The successful integration of thermal energy storage in industrial processes is expected to play an important role in the energy turnaround. Latent heat storage technologies can offer more compact thermal storage at a constant temperature level, in comparison to conventional, sensible thermal storage technologies. The focus of this study is the development of latent heat storage solutions based on the Phase Change Slurry (PCS) concept. Such systems promise higher energy densities both as refrigerants and as storage media while presenting better heat transfer characteristics than conventional latent heat storage technologies. This technology is expected to deliver high thermal power and high-temperature stability which makes it ideal for storage of process heat. An evaluation of important batch processes in industrial applications set the focus on materials with a melting point in the range of 55 - 90 °C. Aluminium ammonium sulfate dodecahydrate (NH₄Al(SO₄)₂·12H₂O) was chosen as the first interesting PCM for the next steps of this study. The ability of this material to produce slurries at the relevant temperatures was demonstrated in a continuous mode in a laboratory test-rig. Critical operational and design parameters were identified.

Keywords: esters, latent heat storage, phase change materials, thermal properties

Procedia PDF Downloads 298

Authors: Ali Siami, Masoud Asayesh, Asghar Najafi, Amirhosein Hamedanian

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There are so many noise sources in power generation units that these sources can produce high-level sound noise. Therefore, sound noise reduction methods can assist these industries, especially in these days that laws related to environmental issues become more strict. In a typical power plant, so many machines and devices with high-level sound noise are arranged beside of each others. Therefore, the sound source identification and reducing the noise level can be very vital. In this paper, the procedure for designing, manufacturing and testing of a silencer-muffler used for a power plant steam vent is mentioned. This unit is placed near the residential area and so it is very important to reduce the noise emission. For this purpose, in the first step, measurements have done to identify the sound source and the frequency content of noise. The overall level of noise was so high and it was more than 120dB. Then, the appropriate noise control device is designed according to the measurement results and operational conditions. In the next step, the designed silencer-muffler has been manufactured and installed on the steam discharge of the ejector. For validation of the silencer-muffler effect, the acoustic test was done again in operating mode. Finally, the measurement results before and after the installation are compared. The results have confirmed a considerable reduction in noise level resultant of using silencer-muffler in the designed frequency range.

Keywords: silencer-muffler, sound noise control, sound measurement, steam ejector

Procedia PDF Downloads 384

Authors: E. Satoh, R. Kasahara, T. Aoki, K. Fukatsu, D. Venkata Ramanarao, H. Harayama, T. Murata, A. Suwa

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Rice plant hoppers (Hemiptera: Delphacidae) have been causing extensive economic damage in rice and are considered as serious threat in rice producing countries of Asia. They have developed resistance to major groups of chemical insecticide, and severe outbreaks occur commonly throughout Asia. To control these nuisance pests, Nihon Nohyaku Co., Ltd., recently discovered an insecticide, benzpyrimoxan (proposed ISO name), which is under development as NNI-1501 (development code). Benzpyrimoxan has a unique chemical structure which contains benzyloxy and cyclic acetal groups on pyrimidine moiety (5-(1,3-dioxan-2-yl)-4-[4- (trifluoromethyl)benzyloxy]pyrimidine). In order to clarify the biological properties of benzpyrimoxan, we conducted several experiments and found the following results. Benzpyrimoxan has high activity against nymphal stages of rice plant hoppers without any adulticidal activity. It provides excellent and long lasting control against rice plant hoppers, including populations that have developed resistance to several other chemical groups of insecticide. The study on its mode of action is undergoing. These features highlight the versatility of this insecticide as an effective and valuable tool from the viewpoints of insecticide resistance management and integrated pest management program. With the use of benzpyrimoxan, farmers shall be able to lead the best yield potential by keeping the population density of rice plant hoppers and associated virus diseases under control.

Keywords: acetal, benzpyrimoxan, insecticide, NNI-1501, pyrimidine, rice plant hoppers

Procedia PDF Downloads 209

Authors: Daniel Hyun

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Dental implants are one of the top 3 reasons to sue a dentist for malpractice. It involves dental implant complications, usually because of the angle of the implant from the surgery. At present, surgeons usually use a 3D-printed navigator that is customized for the patient’s teeth. However, those can’t be reused for other patients as they require time. Therefore, I made a guiding device to assist the surgeon in implant operations. The surgeon can input the objective of the operation, and the device constantly checks if the surgery is heading towards the objective within the set range, telling the surgeon by manipulating the LED. We tested the prototypes’ consistency and accuracy by checking the graph, average standard deviation, and the average change of the calculated angles. The accuracy of performance was also acquired by running the device and checking the outputs. My first prototype used accelerometer and gyroscope sensors from the Arduino MPU6050 sensor, getting a changeable graph, achieving 0.0295 of standard deviations, 0.25 of average change, and 66.6% accuracy of performance. The second prototype used only the gyroscope, and it got a constant graph, achieved 0.0062 of standard deviation, 0.075 of average change, and 100% accuracy of performance, indicating that the accelerometer sensor aggravated the functionality of the device. Using the gyroscope sensor allowed it to measure the orientations of separate axes without affecting each other and also increased the stability and accuracy of the measurements.

Keywords: implant, guide, accelerometer, gyroscope, handpiece

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Hammad Khan, Wookeun Bae

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Major concerns regarding nitritation of low-strength ammonium wastewaters include low ammonium loading rates (usually below 0.2 kg/m3-d) and uncertainty about long-term stability of the process. The purpose of this study was to test a sequencing batch reactor (SBR) filled with cell-immobilized polyethylene glycol (PEG) pellets to see if it could achieve efficient and stable nitritation under various environmental conditions. SBR was fed with synthetic ammonium wastewater of 30±2 mg-N/L and pH: 8±0.05, maintaining the dissolved oxygen concentration of 1.7±0.2 mg/L and the temperature at 30±1oC. The reaction was easily converted to partial nitrification mode within a month by feeding relatively high ammonium substrate (~100 mg-N/L) in the beginning. We observed stable nitritation over 300 days with high ammonium loading rates (as high as ~1.1 kg-N/m3-d), nitrite accumulation rates (mostly over 97%) and ammonium removal rate (mostly over 95%). DO was a major limiting substrate when the DO concentration was below ~4 mg/L and the NH4+-N concentration was above 5 mg/L, giving almost linear increase in the ammonium oxidation rate with the bulk DO increase. Low temperatures mainly affected the reaction rate, which could be compensated for by increasing the pellet volume (i.e. biomass). Our results demonstrated that an SBR filled with small cell-immobilized PEG pellets could achieve very efficient and stable nitritation of a low-strength ammonium wastewater.

Keywords: ammonium loading rate (ALR), cell-immobilization, long-term nitritation, sequencing batch reactor (SBR), sewage treatment

Procedia PDF Downloads 273

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 91

Authors: Yannick Verbelen, Sam De Winne, Niek Blondeel, Ann Peeters, An Braeken, Abdellah Touhafi

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The growing popularity of solid state thermoelectric devices in cooling applications has sparked an increasing diversity of thermoelectric coolers (TECs) on the market, commonly known as “Peltier modules”. They can also be used as generators, converting a temperature difference into electric power, and opportunities are plentiful to make use of these devices as thermoelectric generators (TEGs) to supply energy to low power, autonomous embedded electronic applications. Their adoption as energy harvesters in this new domain of usage is obstructed by the complex thermoelectric models commonly associated with TEGs. Low cost TECs for the consumer market lack the required parameters to use the models because they are not intended for this mode of operation, thereby urging an alternative method to obtain electric power estimations in specific operating conditions. The design of the test setup implemented in this paper is specifically targeted at benchmarking commercial, off-the-shelf TECs for use as energy harvesters in domestic environments: applications with limited temperature differences and space available. The usefulness is demonstrated by testing and comparing single and multi stage TECs with different sizes. The effect of a boost converter stage on the thermoelectric end-to-end efficiency is also discussed.

Keywords: thermoelectric cooler, TEC, complementary balanced energy harvesting, step-up converter, DC/DC converter, energy harvesting, thermal harvesting

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Authors: Xuelin Zhang, Shouxiang Lu, Changhai Li

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The commercial retardant flame polycarbonate samples as the main high speed train interior carriage material with different thicknesses were investigated in Fire Propagation Apparatus with different external heat fluxes under different oxygen concentration from 12% to 40% to study the fire characteristics and quantitatively analyze the ignition time, mass loss rate and heat blockage. The additives of commercial retardant flame polycarbonate were intumescent and maintained a steady height before ignition when heated. The results showed the transformed ignition time (1/t_ig)ⁿ increased linearly with external flux under different oxygen concentration after deducting the heat blockage due to pyrolysis products, the mass loss rate was taken on linearly with external heat fluxes and the slop of the fitting line for mass loss rate and external heat fluxes decreased with the enhanced oxygen concentration and the heat blockage independent on external heat fluxes rose with oxygen concentration increasing. The inquired data as the input of the fire simulation model was the most important to be used to evaluate the fire risk of commercial retardant flame polycarbonate.

Keywords: ignition time, mass loss rate, heat blockage, fire characteristic

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Authors: Borja Bordel, Ramón Alcarria, Marina Pérez

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In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.

Keywords: educational experience, online education, higher education digitalization, COVID, Spain

Procedia PDF Downloads 140

Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

Procedia PDF Downloads 161

Authors: N. Mehrotra, V. Ahuja, N. Sridharan

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Resilience is an all hazard and a proactive approach, require a multidisciplinary input in the inter related variables of the city system. This research based to identify and operationalize indicators for assessment in domain of institutions, infrastructure and knowledge, all three operating in task oriented community networks. This paper gives a brief account of the methodology developed for assessment of Urban Resilience and its prioritized components for a target population within a newly planned urban complex integrating Surajpur and Kasna village as nodes. People’s perception of Urban Resilience has been examined by conducting questionnaire survey among the target population of Greater Noida. As defined by experts, Urban Resilience of a place is considered to be both a product and process of operation to regain normalcy after an event of disturbance of certain level. Based on this methodology, six indicators are identified that contribute to perception of urban resilience both as in the process of evolution and as an outcome. The relative significance of 6 R’ has also been identified. The dependency factor of various resilience indicators have been explored in this paper, which helps in generating new perspective for future research in disaster management. Based on the stated factors this methodology can be applied to assess urban resilience requirements of a well planned town, which is not an end in itself, but calls for new beginnings.

Keywords: disaster, resilience, system, urban

Procedia PDF Downloads 458

Authors: Emmanuel Ifeanyi Ugwu

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Calcium Sulphide which is one of Chalcogenide group of thin films has been analyzed in this work using a theoretical approach in which a scalar wave was propagated through the material thin film medium deposited on a glass substrate with the assumption that the dielectric medium has homogenous reference dielectric constant term, and a perturbed dielectric function, representing the deposited thin film medium on the surface of the glass substrate as represented in this work. These were substituted into a defined scalar wave equation that was solved first of all by transforming it into Volterra equation of second type and solved using the method of separation of variable on scalar wave and subsequently, Green’s function technique was introduced to obtain a model equation of wave propagating through the thin film that was invariably used in computing the propagated field, for different input wavelengths representing UV, Visible and Near-infrared regions of field considering the influence of the dielectric constants of the thin film on the propagating field. The results obtained were used in turn to compute the band gaps, solid state and optical properties of the thin film.

Keywords: scalar wave, dielectric constant, calcium sulphide, solid state, optical properties

Procedia PDF Downloads 118

Authors: Farej Ahmed Emhmmed

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Fracture of duplex stainless steels (DSS) was investigated in air and in 3.5 wt % NaCl solution. Tow sets of fatigued specimens were heat treated at 475ºC for different times and pulled to failure either in air or after kept in 3.5% NaCl with polarization of -900 mV/ SCE. Fracture took place in general by ferrite cleavage and austenite ductile fracture in transgranular mode. Specimens measured stiffness (Ms) was affected by the aging time, with higher values measured for specimens aged for longer times. Microstructural features played a role in "blocking" the crack propagation process leading to lower the CTOD values specially for specimens aged for short times. Unbroken ligaments/ austenite were observed at the crack wake. These features may exerted a bridging stress, blocking effect, at the crack tip giving resistance to the crack propagation process i.e the crack mouth opening was reduced. Higher stress intensity factor Kıc values were observed with increased amounts of crack growth suggesting longer zone of unbroken ligaments in the crack wake. The bridging zone was typically several mm in length. Attempt to model the bridge stress was suggested to understand the role of ligaments/unbroken austenite in increasing the fracture toughness factor.

Keywords: stainless steels, fracture toughness, crack keying effect, ligaments

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Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Amir Shafiq, Asif Shahzad, Shabbar Mehmood, Muhammad Saeed, Hamid Mustafa

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Legislation includes the law or the statutes which is being reputable by a sovereign authority and generally can be implemented by the courts of law time to time to accomplish the objectives. Historically speaking upon the emergence of Pakistan in 1947, the intact laws of the British Raj remained effective after ablution by Islamic Ideology. Thus, there was an intention to begin the statutes book afresh for Pakistan's legal history. In consequence thereof, the process of developing detailed plans, procedures and mechanisms to ensure legislative and regulatory requirements are achieved began keeping in view the cultural values and the local customs. This article is an input to the enduring discussion about implementing rule of law in Pakistan whereas; the rule of law requires the harmony of laws which is mostly in the arrangement of codified state laws. Pakistan has legal plural civilizations where completely different and independent systems of law like the Mohammadan law, the state law and the traditional law exist. The prevailing practiced law in Pakistan is actually the traditional law though the said law is not acknowledged by the State. This caused the main problem of the rule of law in the difference between the state laws and the cultural values. These values, customs and so-called traditional laws are the main obstacle to enforce the State law in true letter and spirit which has caused dissatisfaction of the masses and distrust upon the judicial system of the country.

Keywords: consequences, implement, law, Pakistan

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Authors: Chukwudi Chidume

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This paper considers the symbolism of kola nut according to Igbo worldview. How kola nut helps to shape the people’s philosophical ideology, especially in relation to religion. The roles of kola nut within the Igbo socio-cultural context and the values attached to these roles will be examined. The roles of kola nut as a means of socialization, education and transmission of cultural values from the preceding to succeeding generations will come under consideration. Equally, this paper looks at the traditional rules regarding not only the uses but more essentially the mode of kola nut presentation, blessing, breaking and sharing of kola nut. How these rules and kola nut have persisted in the face of social and cultural changes which have affected the Igbo people shall be reviewed. The roles played by kola nut in Igbo religion will come under study, which is to correct some of the misconceptions by writers who are motivated by eurocentric idealism but quite oblivious of the Igbo cultural setting and the place of kola nut in it. The onslaught of Western civilization causing the change of attitude among the young generation towards kola nut as a vital aspect of our culture tends to pose a threat to the future and survival of kola nut. Again, the study of Igbo culture as many have done rarely gives an in depth knowledge on the concept, roles and symbolism of kola nut as one of the sacred objects like Ofo and Shrines in Igboland. Mostly it is forgotten that without kola nut, shrines cannot be attended to. Many people think that the spiritual significance and sacramental symbolism are not worth exploring. They, therefore, refuse to try and discover the ritual ramifications, claiming that to probe into the mystery demystifies the matter. Kola nut symbolism is not mysteriously inexplicable. It is a revered symbol of social intercourse with deep social relevance.

Keywords: communion, consecration, Igbo, kola nut, religion

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Authors: Siriluk Ruangrungrote

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Analyses of available data from MFR-7 measurement were performed and discussed on the study of tropospheric aerosol and its consequence in Thailand. Since, ASSA (w) is one of the most important parameters for a determination of aerosol effect on radioactive forcing. Here the estimation of w was directly determined in terms of the ratio of aerosol scattering optical depth to aerosol extinction optical depth (ωscat/ωext) without any utilization of aerosol computer code models. This is of benefit for providing the elimination of uncertainty causing by the modeling assumptions and the estimation of actual aerosol input data. Diurnal w of 5 cloudless-days in winter and early summer at 5 distinct wavelengths of 415, 500, 615, 673 and 870 nm with the consideration of Rayleigh scattering and atmospheric column NO2 and Ozone contents were investigated, respectively. Besides, the tendency of spectral dependence of ω representing two seasons was observed. The characteristic of spectral results reveals that during wintertime the atmosphere of the inland rural vicinity for the period of measurement possibly dominated with a lesser amount of soil dust aerosols loading than one in early summer. Hence, the major aerosol loading particularly in summer was subject to a mixture of both soil dust and biomass burning aerosols.

Keywords: aerosol scattering optical depth, aerosol extinction optical depth, biomass burning aerosol, soil dust aerosol

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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Authors: Koswaththage Dilushika Sewwandi, Aminda Lakmal

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From an activity reserved for the privileged few only some decades ago, tourism today moves more than one billion people across international borders each year. As the main part of the tourism industry, MICE tourism came to the floor and nowadays it became the main part of tourism especially in developing countries. Currently due to the fast development projects and infrastructure building, focus on tourism development in Sri Lanka could earn a global identity by practicing MICE tourism especially international conferences. Examine the behavior of conference travelers who looking for Sri Lanka as a conference destination must be required. Since the tourism industry highly involved with the personal factor and the destination selections taken by human beings it is vital to explore the factors affecting to their primary emotions which are shaped up with environmental factors. The Environmental Psychology studies the cognitive and affective behavior of human beings and based on that this study was carried out to examine the impact of environment psychology on customer primary emotions; with special reference to conference travelers to Sri Lanka. Finally, the study concludes with identifying the number of environmental factors as Accommodation, Travel Mode and Hotel Atmosphere that could impact the customer primary emotions of conference travelers to Sri Lanka.

Keywords: MICE tourism, envionmental psychology, primary emotions, destination selection

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Authors: Stephen Olusanmi Akintayo

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Access to safe drinking water remains a major challenge in Nigeria, and where available, the quality of the water is often in doubt. An alternative to the inadequate clean drinking water is being found in treated drinking water packaged in electrically heated sealed nylon and commonly referred to as “sachet water”. “Sachet water” is a common thing in Nigeria as the selling price is within the reach of members of the low socio- economic class and the setting up of a production unit does not require huge capital input. The bacteriological quality of selected “sachet water” stored at room temperature over a period of 56 days was determined to evaluate the safety of the sachet drinking water. Test for the detection of coliform bacteria was performed, and the result showed no coliform bacteria that indicates the absence of fecal contamination throughout 56 days. Heterotrophic plate count (HPC) was done at an interval 14 days, and the samples showed HPC between 0 cfu/mL and 64 cfu/mL. The highest count was observed on day 1. The count decreased between day 1 and 28, while no growths were observed between day 42 and 56. The decrease in HPC suggested the presence of residual disinfectant in the water. The organisms isolated were identified as Staphylococcus epidermis and S. aureus. The presence of these microorganisms in sachet water is indicative for contamination during processing and handling.

Keywords: coliform, heterotrophic plate count, sachet water, Staphyloccocus aureus, Staphyloccocus epidermidis

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Authors: Arman Ameen, Mathias Cehlin

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The use of Building Energy Simulation (BES) software has increased in the last two decades, parallel to the development of increased computing power and easy to use software applications. This type of software is primarily used to simulate the energy use and the indoor environment for a building. The rapid development of these types of software has raised their level of user-friendliness, better parameter input options and the increased possibility of analysis, both for a single building component or an entire building. This, in turn, has led to many researchers utilizing BES software in their research in various degrees. The aim of this paper is to carry out a literature review concerning the use of the BES software IDA Indoor Climate and Energy (IDA ICE) in the scientific community. The focus of this paper will be specifically the use of the software for whole building energy simulation, number and types of articles and publications dates, the area of application, types of parameters used, the location of the studied building, type of building, type of analysis and solution methodology. Another aspect that is examined, which is of great interest, is the method of validations regarding the simulation results. The results show that there is an upgoing trend in the use of IDA ICE and that researchers use the software in their research in various degrees depending on case and aim of their research. The satisfactory level of validation of the simulations carried out in these articles varies depending on the type of article and type of analysis.

Keywords: building simulation, IDA ICE, literature review, validation

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Girish Chavadappanavar

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The impact of climate on agriculture could result in problems with food security and may threaten the livelihood activities upon which much of the population depends. In the present study, the development of a statistical yield forecast model has been carried out for sugarcane production over Belagavi district, Karnataka using weather variables of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of the harvest for sugarcane within an acceptable limit of error. The performance of the model in predicting yields at the district level for sugarcane crops is found quite satisfactory for both validation (2007 and 2008) as well as forecasting (2009 and 2010).In addition to the above study, the climate variability of the area has also been studied, and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and increasing in minimum temperature), while the other three are found in significant with different trends (rainfall and evening time relative humidity with increasing trend and morning time relative humidity with decreasing trend).

Keywords: climate impact, regression analysis, yield and forecast model, sugar models

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Authors: Mohammad Bakhshi, Firas Al Janabi

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High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN Tool, disaggregation, exceedance probability, Kolmogorov-Smirnov test, rainfall

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Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

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Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

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