Search results for: feature selection methods

Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau

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Background: Preparing in the stress field (SF) is, increasingly, a concern for doctors of different specialties. Aims: The aim was to evaluate the importance of an e-learning program for doctors postgraduate courses, in SF. Methods: Doctors (n= 40 male, 40 female) of different specialties and ages (31-71 years), who attended postgraduate courses in SF, voluntarily responded to a questionnaire that included the following themes: Importance of SF courses for specialty practiced by each respondent doctor (using visual analogue scale, VAS); What SF themes would be indicated as e-learning (EL); Preferred form of SF information assimilation: Classical lectures (CL), EL or a combination of these methods (CL+EL); Which information on the SF course are facilitated by EL model versus CL; In their view which are the first four advantages and the first four disadvantages of EL compared to CL, for SF. Results: To most respondents, the SF courses are important for the specialty they practiced (VAS by an average of 4). The SF themes suggested to be done as EL were: Stress mechanisms; stress factor models for different medical specialties; stress assessment methods; primary stress management methods for different specialties. Preferred form of information assimilation was CL+EL. Aspects of the course facilitated by EL versus CL model: Active reading of theoretical information, with fast access to keywords details; watching documentaries in everyone's favorite order; practice through tests and the rapid control of results. The first four EL advantages, mentioned for SF were: Autonomy in managing the time allocated to the study; saving time for traveling to the venue; the ability to read information in various contexts of time and space; communication with colleagues, in good times for everyone. The first three EL disadvantages, mentioned for SF were: It decreases capabilities for group discussion and mobilization for active participation; EL information accession may depend on electrical source or/and Internet; learning slowdown can appear, by temptation of postponing the implementation. Answering questions was partially influenced by the respondent's age and genre. Conclusions: 1) Post-graduate courses in SF are of interest to doctors of different specialties. 2) The majority of participating doctors preferred EL, but combined with CL (CL+EL). 3) Preference for EL was manifested mainly by young or middle age men doctors. 4) It is important to balance the proper formula for chosen EL, to be the most efficient, interesting, useful and agreeable.

Keywords: stress field, doctors’ postgraduate courses, classical lectures, e-learning lecture

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Authors: Muzaffar Hussain

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Requests strategies are considered as a part of the speech acts, which are frequently used in everyday communication. Each language provides speech acts to the speakers; therefore, the selection of appropriate form seems more culture-specific rather than language. The present paper investigates the gender-based difference in the use of request strategies by native speakers of Urdu/Punjabi male and female who are learning English as a second language. The data for the present study were collected from 68 graduate students, who are learning English as an L2 in Pakistan. They were given an online close-ended questionnaire, based on Discourse Completion Test (DCT). After analyzing the data, it was found that the L1 male Urdu/Punjabi speakers were inclined to use more direct request strategies while the female Urdu/Punjabi speakers used indirect request strategies. This paper also found that in some situations female participants used more direct strategies than male participants. The present study concludes that the use of request strategies is influenced by culture, social status, and power distribution in a society.

Keywords: gender variation, request strategies, face-threatening, second language pragmatics, language competence

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Authors: Agnieszka Misztal

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The popularity of the quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with the demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel appropriate to focus attention on the selection of companies aspiring to quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car), 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). Identified determinants were divided in two types of criteria into: internal and external, as well as: hard and soft. The article presents hard - technical factors that automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: automotive industry, quality management system, automotive technology, automotive company

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Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy

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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared together

Keywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Avijit Sengupta, Klarissa Ting Ting Cheng, Maffee Peng-Hui Wan

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This study investigates the influence of user factors and referent characteristics on representation types generated using the stereotype production method for designing icons. Sixty-eight participants of farming communities were asked to draw images based on sixteen feature referents. Significant statistical differences were found between the types of representations generated for contextual and context-independent referents. Strong correlations were observed between years of formal education and total number of abstract representations produced for both contextual and context-independent referents. However, representation characteristics were not influenced by other user factors such as participants’ experience with mobile phone and years of farming experience. A statistically significant tendency of making concrete representations was observed for both contextual and context-independent referents. These findings provide insights on community members’ involvement in icon design and suggest a consolidated icon design strategy based on population stereotype, particularly for under-served rural communities of India.

Keywords: abstract representation, concrete representation, participatory design, population stereotype

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Authors: Zeljko Crljen, Predrag Lazic

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Graphene has attracted a tremendous interest in the field of nanoelectronics and spintronics due to its exceptional electronic properties. However, pristine graphene has no band gap, a feature needed in building some of the electronic elements. Recently, a growing attention has been given to a class of carbon allotropes of graphene with honeycomb structures, in particular to graphyne and graphdiyne. They are characterized with a single and double acetylene bonding chains respectively, connecting the nearest-neighbor hexagonal rings. With an electron density comparable to that of graphene and a prominent gap in electronic band structures they appear as promising materials for nanoelectronic components. We studied the electronic structure and transport of infinite sheets of graphyne and graphdiyne and compared them with graphene. The method based on the non-equilibrium Green functions and density functional theory has been used in order to obtain a full ab initio self-consistent description of the transport current with different electrochemical bias potentials. The current/voltage (I/V) characteristics show a semi-conducting behavior with prominent nonlinearities at higher voltages. The calculated band gaps are 0.52V and 0.59V, respectively, and the effective masses are considerably smaller compared to typical semiconductors. We analyzed the results in terms of transmission eigenchannels and showed that the difference in conductance is directly related to the difference of the internal structure of the allotropes.

Keywords: electronic transport, graphene-like structures, nanoelectronics, two-dimensional materials

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Authors: Li Zhang, Yuehong Su

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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

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Authors: Konstantinos G. Papaioannou, Panagiotis K. Serdaris

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This study, examines the level of implementation of Human Resource Management (HRM) activities in law enforcement agencies in Greece. Recognizing that HRM is crucial for maximizing organizational performance, the study aims to evaluate its application within Greek law enforcement. A quantitative-descriptive survey was conducted, involving 996 executives from Greek Law Enforcement Agencies (477 from the Hellenic Police and 519 from the Hellenic Coast Guard), through random sampling. The survey, revealed significant concerns regarding the minimal implementation of HRM practices, in both agencies. The findings indicate that HRM practices, such as HR planning, recruitment, job position, selection, training and development, personnel management, compensation, labor relations and health and safety, are minimally applied. Neither the Hellenic Police nor the Hellenic Coast Guard appears to follow a comprehensive HRM plan. The study, contributes both theoretically and practically by highlighting the lack of HRM implementation in these agencies. The data suggest that by adopting strategic HRM practices, these organizations can enhance personnel performance and better fulfill their societal roles. Future research should extend to law enforcement agencies in other countries to draw more representative conclusion.

Keywords: coastguard, human resources management, law enforcement agencies, performance management, police

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Authors: Zandi Ahmad, Sokhanguei Yahya, Saboonchi Reza

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Objective: The new and modern lifestyle, especially in the twenty-first century and lack of movement in spinal structure have made patients and the physicians in the field of health and also other insurance companies in the developed and developing countries worry more than before about the abnormalities of spinal column- this great healthcare problem. The high prevalence of spinal column in all age groups -from children to adults- and in all professions have led the researchers to the idea of giving an opportunity to all those who worry about the dangers threatening the spinal column. Therefore, one of the corrective methods for these patients is using SEAS exercises. Materials and Methods: This study aims at investigating the effect of one-period of SEAS exercises on some spinal biomechanical and postural parameters in the students with idiopathic scoliosis. According to the nature of the study and research objectives as well as the data collection methods, the current research is a semi-empirical survey. The research population is comprised of students with idiopathic scoliosis. A total number of 30 students were selected using available sampling and divided into two groups of control and SEAS exercises. Scoliometer was used for data collection. Descriptive statistics were used to categorize the findings. Kolmogorov-Smirnov statistical models were used to confirm that the distribution of the data is normal and T-test was used for effectiveness. Hypothesis testing was done using SPSS21. Conclusion: Results show that SEAS exercises have a significant effect in Adam’s Test. Therefore, according to the obtained results, SEAS exercises can be used to recover idiopathic scoliosis among the students. Further studies in larger samples and treatment, periods as well as more follow-up investigations appear to be essential to prove these effects.

Keywords: SEAS exercises, idiopathic scoliosis, Adam’s test, exercise

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Authors: Jai Hyung Park, Eugene Kim, Jin Hun Park, Min Joon Oh

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Introduction: Subchondral insufficiency fracture of the femoral head (SIF) is a rare complication; however, it has been recognized to cause femoral head collapse. Subchondral insufficiency fracture (SIF) is caused by normal or physiological stress without any trauma. It has been reported in osteoporotic patients after the fixation of the proximal femur with an Intramedullary nail. Case presentation: We reported 5 cases with SIF of the femoral head after proximal femur fracture fixation with Intra-medullary nail. All patients had osteoporosis as an underlying disease. Good reduction was achieved in all 5 patients. SIF was found from about 3 months to 4 years after the initial operation, and all the fractures were solidly united at the final diagnosis. We investigated retrospectively the feature of those cases and several factors that affected the occurrence of SIF. Discussion: There are a few discussions regarding the SIF of the femoral head. These discussions may include the predisposing risk factors, how to diagnose the SIF in osteoporotic patients, and the peri-operative factors to prevent SIF. Conclusion: Subchondral insufficiency fracture of the femoral head is a considerable complication after the internal fixation of the proximal femur. There are several factors that can be modified. If they could be controlled in the peri-operative period, SIF could be prevented or handled in advance. Other options related to arthroplasty can be considered in old osteoporotic patients.

Keywords: insufficiency fracture of femoral head, intra-medullary nail, osteoporosis, proximal femur fracture

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Authors: Hamed Sarbazy, Zohre Gholipour Haftkhani, Ali Safari, Pejman Hosseiniun

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Scientific and industrial progress in the past two decades has resulted in energy distribution systems based on power electronics, as an enabling technology in various industries and building management systems can be considered. Grading and standardization module power electronics systems and its use in a distributed control system, a strategy for overcoming the limitations of using this system. The purpose of this paper is to investigate strategies for scheduling and control structure of standard modules is a power electronic systems. This paper introduces the classical control methods and disadvantages of these methods will be discussed, The hierarchical control as a mechanism for distributed control structure of the classification module explains. The different levels of control and communication between these levels are fully introduced. Also continue to standardize software distribution system control structure is discussed. Finally, as an example, the control structure will be presented in a DC distribution system.

Keywords: application management, hardware management, power electronics, building blocks

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

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This paper shortly describes biomass types and growing amount in the Czech Republic. The considerable part of this paper deals with energy parameters of the most frequent utilizing biomass types and results of their gasification testing. There was chosen sixteen the most exploited "Czech" woody plants and grasses. There were determinated raw, element and biochemical analysis, basic calorimetric values, ash composition and ash characteristic temperatures. After that, each biofuel was tested by fluid bed gasification. The essential part of this paper yields results of chosen biomass types gasification experiments. Partly, there are described an operating conditions in detail with accentuation of individual fuels particularities partly, there is summarized gas composition and impurities content. The essential difference was determined mainly between woody plants and grasses both from point of view of the operating conditions and gas quality. The woody plants was evaluated as more suitable fuels for fluid bed gasifiers. This results will be able to significantly help with decision which energy plants are suitable for growing or with optimal biomass-treatment technology selection.

Keywords: biomass growing, biomass types, gasification, biomass fuels

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Authors: Mohammad Ali Badri, Pouya Molana, Amin Rezvanpour

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In this paper, planning catamaran and mono-hull vessels resistance and trim in calm waters were considered. Hydrodynamic analysis of fast mono-hull planning vessel was also investigated. In order to hull form geometry optimization, numerical methods of different parameters were used for this type of vessels. Hull material was selected in carbon fiber composite. Exact architectural aspects were specified and stability calculations were performed as well. Hydrodynamic calculations to extract the resistance force using semi-analytical methods and numerical modeling were carried out. Free surface numerical analysis of vessel in designed draft using finite volume method and double phase were evaluated and verified by experimental tests.

Keywords: fast vessel, hydrostatic and hydrodynamic optimization, free surface flow, computational fluid dynamics

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Authors: Faizah Almalki, Simeon Gill, Steve G. Hayes, Lisa Taylor

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A core element of cultural identity is the traditional costumes that provide insight into the heritage that has been acquired over time. This heritage is apparent in the use of colour, the styles and the functions of the clothing and it also reflects the skills of those who created the items and the time taken to produce them. Modern flat pattern drafting methods for making garment patterns are simple in comparison to the relatively laborious traditional approaches that would require personal interaction with the wearer throughout the production process. The current study reflects on the main elements of the pattern cutting system and how this has evolved in Saudi Arabia to affect the design of the Sawan garment. Analysis of the traditional methods for constructing Sawan garments was undertaken through observation of the practice and the garments and consulting documented guidance. This provided a foundation through which to explore how modern technology can be applied to improve the process. In this research, modern methods are proposed for producing traditional Saudi garments more efficiently while retaining elements of the conventional style and design. The current study has documented the vital aspects of Sawan garment style. The result showed that the method had been used to take the body measurements and pattern making was elementary and offered simple geometric shape and the Sawan garment is composed of four pieces. Consequently, this research allows for classical pattern shapes to be embedded in garments now worn in Saudi Arabia and for the continuation of cultural heritage.

Keywords: traditional Sawan garment technique, modern pattern cutting technique, the shape of the garment and software, Lectra Modaris

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Authors: Latika Choudhary

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“The potential benefits of Artificial Intelligence are huge, So are the dangers.” - Dave Water. Artificial intelligence is one of the facet of Information technology domain which despite several attempts does not have a clear definition or ambit. However it can be understood as technology to solve problems via automated decisions and predictions. Artificial intelligence is essentially an algorithm based technology which analyses the large amounts of data and then solves problems by detecting useful patterns. Owing to its automated feature it will not be wrong to say that humans & AI have more utility than humans alone or computers alone.1 For many decades AI experienced enthusiasm as well as setbacks, yet it has today become part and parcel of our everyday life, making it convenient or at times problematic. AI and related technology encompass Intellectual Property in multiple ways, the most important being AI technology for management of Intellectual Property, IP for protecting AI and IP as a hindrance to the transparency of AI systems. Thus the relationship between the two is of reciprocity as IP influences AI and vice versa. While AI is a recent concept, the IP laws for protection or even dealing with its challenges are relatively older, raising the need for revision to keep up with the pace of technological advancements. This paper will analyze the relationship between AI and IP to determine how beneficial or conflictual the same is, address how the old concepts of IP are being stretched to its maximum limits so as to accommodate the unwanted consequences of the Artificial Intelligence and propose ways to mitigate the situation so that AI becomes the friend it is and not turn into a potential foe it appears to be.

Keywords: intellectual property rights, information technology, algorithm, artificial intelligence

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Authors: Aladdin Al-Tarawneh

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The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.

Keywords: Quran translation, hybrid approach, domestication, foreignization, hybrid model

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Authors: Marulasiddappa H. B., Pushparajesh Viswanathan

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Day by day, the uses of internal combustion engines (ICE) are deteriorating because of pollution and less fuel availability. In the present scenario, the electric vehicle (EV) plays a major role in the place of an ICE vehicle. The performance of EVs can be improved by the proper selection of electric motors. Initially, EV preferred induction motors for traction purposes, but due to complexity in controlling induction motor, permanent magnet synchronous motor (PMSM) is replacing induction motor in EV due to its advantages. Direct torque control (DTC) is one of the known techniques for PMSM drive in EV to control the torque and speed. However, the presence of torque ripple is the main drawback of this technique. Many control strategies are followed to reduce the torque ripples in PMSM. In this paper, the adaptive neuro-fuzzy inference system (ANFIS) controller technique is proposed to reduce torque ripples and settling time. Here the performance parameters like torque, speed and settling time are compared between conventional proportional-integral (PI) controller with ANFIS controller.

Keywords: direct torque control, electric vehicle, torque ripple, PMSM

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Authors: Ada Adoga James

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This paper discussed the concept of community participation and identified tertiary education problems; strategies and methods communities could be involved to reduce conflict witnessed in our tertiary institutions of learning due to government inability to fund education. The paper pointed out that community participation through the use of Parent Teachers Association (PTA), age grade, traditional leaders, village based associations, religious and political organs could be sensitized to raise financial resources. The paper identified different sources of conflicts, the outcome of which causes prolonged academic activities, destruction of lives and properties and in some cased render school environment completely insecure for serious academic activities. It recommends involvement of community participation in assisting government, proper handling of tertiary institutions in management, and more democratic procedure in conflict resolution like cordial relationship between staff, students and trade unions in decision making process.

Keywords: community, conflict resolution, tertiary education, psychology, psychiatry

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Authors: Hamdan Arief Hanif, Rahmat Sidiq

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Indonesia is a country of law, the legal system adopted by Indonesia is a civil law system. A major feature of the civil law is the codified legislation. Meanwhile the majority of society Indonesia are Muslims, whilst Islamic law itself having the sources written in Qur'an, Sunnah and the opinion of Muslim scholars, generally not codified in book form of legislation that is easy on the set as a reference. in Indonesia, many scholars have different opinions in decisions so that there is no legal certainty in Muslim civil cases, so the need for legal codification, which, as the source of the judges in deciding a case, especially a case in religious courts. This paper raised the topic of discussion which offers a solution to the application of the codification of the Islamic Law which became the core resources in delivering a verdict against Islamic civil related issue; codification usually called a compilation of Islamic Law. Compilation of Islamic Law is highly recommended as a core reference for the judges in religious courts in Indonesia. This compilation which includes a collection of large number of opinions scholars (book of fiqh) that existed previously and are ripened in deduce in order to unify the existing differences. This paper also discusses how the early formation of the compilation and as the right solution in order to create legal certainty and justice especially for the muslim community in Indonesia.

Keywords: Islamic law, compilation, law applied core, religious court

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Yuheng Tao

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Rapid urbanization has brought the consequences of incompatible and excessive homogeneity of urban system, and urban color planning has become one of the most effective ways to restore the characteristics of cities. Among the many urban color design research, the establishment of urban theme colors has rarely been discussed. This study took the "New Taipei City Environmental Aesthetic Color” project as a research case and conducted mixed-method research that included expert interviews and quantitative survey data. This study introduces how theme colors were selected by the experts and investigates public’s perception and preference of the selected theme colors. Several findings include 1) urban memory plays a significant role in determining urban theme colors; 2) When establishing urban theme colors, areas/cities with relatively weak urban memory are given priority to be defined; 3) Urban theme colors that imply cultural attributes are more widely accepted by the public; 4) A representative city theme color helps conserve culture rather than guiding innovation. In addition, this research rearranges the urban color symbolism and specific content of urban theme colors and provides a more scientific urban theme color selection scheme for urban planners.

Keywords: urban theme color, urban color attribute, public perception, public preferences

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Authors: Seyed Mehran Kazemi, Bahare Fatemi

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Sudoku is a logic-based combinatorial puzzle game which is popular among people of different ages. Due to this popularity, computer softwares are being developed to generate and solve Sudoku puzzles with different levels of difficulty. Several methods and algorithms have been proposed and used in different softwares to efficiently solve Sudoku puzzles. Various search methods such as stochastic local search have been applied to this problem. Genetic Algorithm (GA) is one of the algorithms which have been applied to this problem in different forms and in several works in the literature. In these works, chromosomes with little or no information were considered and obtained results were not promising. In this paper, we propose a new way of applying GA to this problem which uses more-informed chromosomes than other works in the literature. We optimize the parameters of our GA using puzzles with different levels of difficulty. Then we use the optimized values of the parameters to solve various puzzles and compare our results to another GA-based method for solving Sudoku puzzles.

Keywords: genetic algorithm, optimization, solving Sudoku puzzles, stochastic local search

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

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The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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Authors: Asmau Mukhtar Ahmed, Olga Duran

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Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

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Authors: Sajedeh Salehi, Marco Giacalone

Abstract:

This paper examines the role of existing online dispute resolution (ODR) mechanisms and their effects on ameliorating access to justice – as a protected right by Art. 47 of the EU Charter of Fundamental Rights – for consumers in EU. The major focus of this study will be on evaluating ODR as the means of dispute resolution for Business-to-Consumer (B2C) cross-border small claims raised in e-commerce transactions. The authors will elaborate the consequences of implementing ODR methods in the context of recent developments in EU regulatory safeguards on promoting consumer protection. In this analysis, both non-judiciary and judiciary ODR redress mechanisms are considered, however, the significant consideration is given to – obligatory and non-obligatory – judiciary ODR methods. For that purpose, this paper will particularly investigate the impact of the EU ODR platform as well as the European Small Claims Procedure (ESCP) Regulation 861/2007 and their role on accelerating the access to justice for consumers in B2C e-disputes. Although, considerable volume of research has been carried out on ODR for consumer claims, rather less (or no-) attention has been paid to provide a combined doctrinal and empirical evaluation of ODR’s potential in resolving cross-border small e-disputes, in EU. Hence, the methodological approach taken in this study is a mixed methodology based on qualitative (interviews) and quantitative (surveys) research methods which will be mainly based on the data acquired through the findings of the Small Claims Analysis Net (SCAN) project. This project contributes towards examining the ESCP Regulation implementation and efficiency in providing consumers with a legal watershed through using the ODR for their transnational small claims. The outcomes of this research may benefit both academia and policymakers at national and international level.

Keywords: access to justice, consumers, e-commerce, small e-Disputes

Procedia PDF Downloads 124

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

Abstract:

Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 539

Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

Abstract:

Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Mudavath Raju, Bhaskar Gugulothu, B. Rajendra Naik

Abstract:

The rapid advances in Very Large Scale Integration (VLSI) technology has resulted in the reduction of minimum feature size to sub-quarter microns and switching time in tens of picoseconds or even less. As a result, the degradation of high-speed digital circuits due to signal integrity issues such as coupling effects, clock feedthrough, crosstalk noise and delay uncertainty noise. Crosstalk noise in VLSI interconnects is a major concern and reduction in VLSI interconnect has become more important for high-speed digital circuits. It is the most effectively considered in Deep Sub Micron (DSM) and Ultra Deep Sub Micron (UDSM) technology. Increasing spacing in-between aggressor and victim line is one of the technique to reduce the crosstalk. Guard trace or shield insertion in-between aggressor and victim is also one of the prominent options for the minimization of crosstalk. In this paper, far end crosstalk noise is estimated with mutual inductance and capacitance RLC interconnect model. Also investigated the extent of crosstalk in capacitive and inductively coupled interconnects to minimizes the same through shield insertion technique.

Keywords: VLSI, interconnects, signal integrity, crosstalk, shield insertion, guard trace, deep sub micron

Procedia PDF Downloads 177