Search results for: gaussian selection operator

Authors: Abdulmumin Isah

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Over the years, researchers have employed different approaches in the study of usage of library services in the traditional library system, such approaches have provided explanations on the users’ perception, attitude, and usage of library services. Findings of such studies which often employed survey research approach have guided librarians and library stakeholders in their drive to improve library services to patrons. However, with the advent of digital library services, librarians and information science researchers have been experiencing methodological issues in the study of digital library services. While some quantitative approaches have been employed to understand adoption and usage of digital library services, conflicting results from such studies have increased the need to employ qualitative approaches. The appropriateness of the qualitative approaches has also been questioned. This study intends to review methodological approaches in the studies of digital libraries and provides a framework for the selection of appropriate research approach for the study of digital libraries using Nigerian university systems as case study.

Keywords: digital library, university library, methodological issues, research approaches, quantitative, qualitative, Nigeria

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Authors: Ezgi Yurdakul, Klaus-Alexander Rieder, Richard Sibbick

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Most of the shotcrete projects require compliance with meeting a specified early-age strength target (e.g., reaching 1 MPa in 1 hour) that is selected based on the underground conditions. To meet the desired early-age performance characteristics, accelerators are commonly used as they increase early-age strength development rate and accelerate the setting thereby reducing sagging and rebound. The selection of accelerator type and its dosage is made by the setting time and strength required for the shotcrete application. While alkaline and alkali-free accelerators are the two main types used in wet-mix shotcrete; alkali-free admixtures increasingly substitute the alkaline accelerators to improve the performance and working safety. This paper aims to evaluate the impact of alkali-free accelerators in wet-mix on various tests including set time, early and later-age compressive strength, boiled absorption, and electrical resistivity. Furthermore, the comparison between accelerated and non-accelerated samples will be made to demonstrate the interaction between cement and accelerators. Scanning electron microscopy (SEM), fluorescent resin impregnated thin section and cut and polished surface images will be used to understand the microstructure characterization of mixes in the presence of accelerators.

Keywords: accelerators, chemical admixtures, shotcrete, sprayed concrete

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Authors: A. H. Elkholy, D. M. Almutairi

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The successful and efficient execution of a forging process is dependent upon the correct analysis of loading and metal flow of blanks. This paper investigates the Upper Bound Technique (UBT) and its application in the analysis of open forging process when a possibility of blank bulging exists. The UBT is one of the energy rate minimization methods for the solution of metal forming process based on the upper bound theorem. In this regards, the kinematically admissible velocity field is obtained by minimizing the total forging energy rate. A computer program is developed in this research to implement the UBT. The significant advantages of this method is the speed of execution while maintaining a fairly high degree of accuracy and the wide prediction capability. The information from this analysis is useful for the design of forging processes and dies. Results for the prediction of forging loads and stresses, metal flow and surface profiles with the assured benefits in terms of press selection and blank preform design are outlined in some detail. The obtained predictions are ready for comparison with both laboratory and industrial results.

Keywords: forging, upper bound technique, metal forming, forging energy, forging die/platen

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Authors: Noshaba Dilbar, Maria Jabbar

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Medicinal plants are considered to be the richest source of drug discovery. The main cause of medicinal properties of plants is the presence of bioactive compounds in them. Phytochemical screening is the valuable process that detects bioactive compounds(secondary metabolites) in plants. The present study was carried out to determine phytochemical profile and ethnobotanical importance of Capparidaceae species. ( Capparis spinosa and Dipterygium glaucum). The selection of plants was made on basis of traditional knowledge of their usage in ayurvedic medicines. Different type of solvents(ethanol, methanol, chloroform, benzene and petroleum ether) were used to make extracts of dry and fresh plants. Phytochemical screening was made by using various standard techniques. Results reveal the presence of large range of bioactive compounds i.e alakloids, saponins, flavonoids, terpenoids, glycosides, phenols and steroids. Methanol, petroleum ether and chloroform extracts showed high extractability of bioactive compounds. The results obtained ensure these plants a reliable source of pharmacological industry and can be used in making of various biological friendly drugs.

Keywords: bioactive compounds, Capparidaceae, phytochemical screening, secondary metabolites

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Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

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Authors: Amit Bhattacharyya

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The economic scenario of any region does not show the real picture for the measurement of overall development. Therefore, economic development must be accompanied by social development to be able to make an assessment to measure the level of development. The spatial variation with respect to social development has been discussed taking into account the quality of functioning of a social system in a specific area. In this paper, an attempt has been made to study the spatial distribution of social infrastructural facilities and analyze the magnitude of regional disparities at inter- block level in Barddhman district. It starts with the detailed account of the selection process of social infrastructure indicators and describes the methodology employed in the empirical analysis. Analyzing the block level data, this paper tries to identify the disparity among the blocks in the levels of social development. The results have been subsequently explained using both statistical analysis and geo spatial technique. The paper reveals that the social development is not going on at the same rate in every part of the district. Health facilities and educational facilities are concentrated at some selected point. So overall development activities come to be concentrated in a few centres and the disparity is seen over the blocks.

Keywords: disparity, inter-block, social development, spatial variation

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Zhang Jiafeng

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Stone houses, represented by Shitang town, Wenling town, Taizhou city, are very precious cultural relics in Zhejiang province and even in the whole country. The coastal residences in eastern Zhejiang with distinctive regional characteristics are completely different from the traditional residential styles in the inland areas of Zhejiang. However, with the aggravation of the conflict between the use function of traditional stone houses and the modern lifestyle, and the lack of effective protection, stone houses are disappearing in large numbers. Therefore, it is very important to protect and inherit the stone house building, and make effective and feasible development strategies. This paper will analyze the formation background, location selection, plane layout, architectural form, spatial organization, material application, and construction technology of the stone houses through literature research and field investigation. In addition, a series of feasibility studies are carried out on the protection and renovation of stone houses. The ultimate purpose is to attract people's attention and provide some reference for the protection, inheritance, development, and utilization of traditional houses in coastal areas.

Keywords: regional, stone house building, traditional houses, Wenling Shitang

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Authors: Kiurski S. Jelena, Ranogajec G. Jonjaua, Kecić S. Vesna, Oros B. Ivana

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The present study investigates the effectiveness of newly designed clayey pellets (fired clay pellets diameter sizes of 5 and 8 mm, and unfired clay pellets with the diameter size of 15 mm) as the beds in the column adsorption process. The adsorption experiments in the batch mode were performed before the column experiment with the purpose to determine the order of adsorbent package in the column which was to be designed in the investigation. The column experiment was performed by using a known mass of the clayey beds and the volume of the waste printing developer, which was purified. The column was filled in the following order: fired clay pellets of the diameter size of 5 mm, fired clay pellets of the diameter size of 8 mm, and unfired clay pellets of the diameter size of 15 mm. The selected order of the adsorbents showed a high removal efficiency for zinc (97.8%) and copper (81.5%) ions. These efficiencies were better than those in the case of the already existing mode adsorption. The obtained experimental data present a good basis for the selection of an appropriate column fill, but further testing is necessary in order to obtain more accurate results.

Keywords: clay materials, fix bed adsorption column, metal ions, printing developer

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Authors: Marco Camilli

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This article examines the impact of the pandemic outbreak of COVID-19 in the tourism sector in Italy, analyzing the current scenario, the government decisions and the private company reaction for the summer season 2020. The framework of the data analyzed shows how massive it’s the impact of the pandemic outbreak in the tourism revenue, and the weaknesses of the measures proposed. Keywords Travel &Tourism, Transportation, Sustainability, COVID-19, Businesses Introduction The current COVID-19 scenario shows a shocking situation for the tourism and transportation sectors: it could be the most affected by the Coronavirus in Italy. According to forecasts, depending on the duration of the epidemic outbreak and the lockdown strategy applied by the Government, businesses in the supply chain could lose between 24 and 66 billion in turnover in the period of 2020-21, with huge diversified impacts at the national and regional level. Many tourist companies are on the verge of survival and if there are no massive measures by the government they risk closure. Data analysis The tourism and transport sector could be among the sectors most damaged by Covid-19 in Italy. Considering the two-year period 2020-21, companies operating in the travel & tourism sector (Tour operator, Travel Agencies, Hotel, Guides, Bus Company, etc..) could in suffer losses in revenues of 24 to 64 billion euros, especially in the sectors such as the travel agencies, hotel and rental. According to Statista Research Department, from April 2020 estimated that the coronavirus (COVID-19) pandemic will have a significant impact on revenues of the tourism industry in Italy. Revenues are expected to decrease by over 40 billion euros in the first semester of 2020, compared to the same period of the previous year. According to the study, hotel and non-hotel accommodations will experience the highest loss. Revenues of this sector are expected to decrease by 13 billion euros compared to the first semester of 2019 when accommodations registered revenues for about 17 billion euros. According to Statista.com, in 2020, Italy is expected to register a decrease of roughly 28.5 million tourist arrivals due to the impact of coronavirus (COVID-19) on the country's tourist sector. According to the estimate, the region of Veneto will record the highest drop with a decrease of roughly 4.61 million arrivals. Similarly, Lombardy is expected to register a decrease of about 3.87 million arrivals in 2020.

Keywords: travel and tourism, sustainability, COVID-19, businesses, transportation

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Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor

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Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.

Keywords: additive parameter, angular softmax, speaker verification, PLDA

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Authors: Ashraf Ward

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Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

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Authors: Mudawamah Mudawamah, Muhammad Z. Fadli, Gatot Ciptadi, Aulanni’am

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Canary breeders have spread throughout Indonesian regions for the low-middle society and become an income source for them. The interesting phenomenon of the canary market is the feather colours become one of determining factor for the price. The advantages of this research were contributed to the molecular database as a base of selection and mating for the Indonesia canary breeder. The research method was experiment with the genome obtained from canary blood isolation. The genome did the PCR amplification with PMEL marker followed by sequencing. Canaries were used 24 heads of light and dark colour feathers. Research data analyses used BioEdit and Network 4.6.0.0 software. The results showed that all samples were amplification with PMEL gene with 500 bp fragment length. In base sequence of 40 was found Cytosine(C) in the light colour canaries, while the dark colour canaries was obtained Thymine (T) in same base sequence. Sequence results had 286-415 bp fragment and 10 haplotypes. The conclusions were the PMEL gene (gene of white pigment) was likely to be used PMEL gene to detect molecular genetic variation of dark and light colour feather.

Keywords: canary, haplotype, PMEL, sequence

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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: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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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: 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: 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: 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: 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: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: Yani Shi, Jiaqi Yan

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A new product is important for companies to extend consumers and manifest competitiveness. New product often involves new features that consumers might not be familiar with while it may also have a competitive advantage to attract consumers compared to established products. However, although most online retailers employ recommendation agents (RA) to influence consumers’ product choice decision, recommended new products are not accepted and chosen as expected. We argue that it might also be caused by providing a new product recommendation in the wrong way at the wrong time. This study seeks to discuss how new product evaluations sourced from third parties could be employed in RAs as evidence of the superiority for the new product and how the new product recommendation could be provided to a consumer at the right time so that it can be accepted and finally chosen during the consumer’s decision-making process. A 2*2 controlled laboratory experiment was conducted to understand the selection of new product recommendation sources and recommendation timing. Human subjects were randomly assigned to one of the four treatments to minimize the effects of individual differences on the results. Participants were told to make purchase choices from our product categories. We find that a new product recommended right after a similar existing product and with the source of the expert review will be more likely to be accepted. Based on this study, both theoretical and practical contributions are provided regarding new product recommendation.

Keywords: new product recommendation, recommendation timing, recommendation source, recommendation agents

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Authors: Peter Fedichev

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We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

Abstract:

Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

Procedia PDF Downloads 385

Authors: Dagnija Blumberga, Toms Prodanuks, Ivars Veidenbergs, Andra Blumberga

Abstract:

Gas condensing units with inner tubes heat exchangers represent third generation technology and differ from second generation heat and mass transfer units, which are fulfilled by passive filling material layer. The first one improves heat and mass transfer by increasing cooled contact surface of gas and condensate drops and film formed in inner tubes heat exchanger. This paper presents a selection of significant factors which influence the heat and mass transfer. Experimental planning is based on the research and analysis of main three independent variables; velocity of water and gas as well as density of spraying. Empirical mathematical models show that the coefficient of heat transfer is used as dependent parameter which depends on two independent variables; water and gas velocity. Empirical model is proved by the use of experimental data of two independent gas condensing units in Lithuania and Russia. Experimental data are processed by the use of heat transfer criteria-Kirpichov number. Results allow drawing the graphical nomogram for the calculation of heat and mass transfer conditions in the innovative and energy efficient gas cooling unit.

Keywords: gas condensing unit, filling, inner heat exchanger, package, spraying, tunes

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Authors: Usman Adekunle Ojedokun, Adeyinka Abideen Aderinto

Abstract:

Migration remains an important course of action often resort-to by human and some other classes of animal for survival in the face of life-threatening conditions. However, the activity of certain group of immigrants, who are exploiting the socio-economic and environmental challenges in their home countries to conduct street begging across different countries in Africa, is fast becoming a major cause for concern. This paper examined the migratory trajectory of transnational street beggars in South Western, Nigeria. Strain and Migration Network Theories were adopted for the study. The methods of data collection were survey questionnaire, in-depth interview, and key informant interview. Convenience and purposive sampling techniques were employed for the selection of 395 transnational street beggars and 4 key informants were purposively chosen. Findings revealed that transnational street beggars immigrated into Nigeria all year round and all of them came by road. Also, while some of them entered the country officially, others gained entry illegally. The majority (29.3%) arrived through Sokoto, a border State to some neighbouring countries. This study calls for more security measures at the Nigerian borders as a way of controlling the influx of this category of beggars into the country.

Keywords: transnational street beggars, street begging, migration, Nigeria

Procedia PDF Downloads 261

Authors: S. P. Praveen Kumar, Bong-Su Sin, Kwon-Hee Lee

Abstract:

Finned-tube heat exchangers are predominantly used in space conditioning systems, as well as other applications requiring heat exchange between two fluids. The design of finned-tube heat exchangers requires the selection of over a dozen design parameters by the designer such as tube pitch, tube diameter, tube thickness, etc. Finned-tube heat exchangers are common devices; however, their performance characteristics are complicated. In this paper, numerical studies have been carried out to analyze the performances of finned tube heat exchanger (without fins considered for experimental purpose) by predicting the characteristics of temperature difference and pressure drop. In this study, a design considering 5 design variables, maximizing the temperature difference and minimizing the pressure drop was suggested by applying DOE. In this process, L18 orthogonal array was adopted. Parametric analytical studies have been carried out using Analysis of Variance (ANOVA) to determine the relative importance of each variable with respect to the temperature difference and the pressure drop. Following the results, the final design was suggested by predicting the optimum design therefore confirming the optimized condition.

Keywords: heat exchanger, fluid analysis, heat transfer, design of experiment, analysis of variance

Procedia PDF Downloads 446