Search results for: customer segments

Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Won Man Park, Dae Kyung Choi, Kyungsoo Kim, Yoon Hyuk Kim

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Traction therapy has been used in the treatment of spinal pain for decades. However, a case study reported the occurrence of large disc protrusion during motorized traction therapy. In this study, we hypothesized that additional local decompression with a global axial traction could be helpful for risk reduction of intervertebral disc damage. A validated three dimensional finite element model of the lumbar spine was used. Two-step traction therapy using the axial global traction (the first step) with 1/3 body weight and the additional local decompression (the second step) with 7 mm translation of L4 spinal bone was determined for the traction therapy. During two-step traction therapy, the sacrum was constrained in all translational directions. Reduced lordosis angle by the global axial traction recovered with the additional local decompression. Stress on fibers of the annulus fibrosus by the axial global traction decreased with the local decompression by 17%~96% in the posterior region of intervertebral disc. Stresses on ligaments except anterior longitudinal ligaments in all motion segments decreased till 4.9 mm~5.6 mm translation of L4 spinal bone. The results of this study showed that the additional local decompression is very useful for reducing risk of damage in the intervertebral disc and ligaments caused by the global axial traction force. Moreover, the local decompression could be used to enhance reduction of intradiscal pressure.

Keywords: lumbar spine, traction-therapy, biomechanics, finite element analysis

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Authors: Evy Latifah, Eli Korlina, Hanik Anggraeni, Kuntoro Boga, Joko Mariyono

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During the rainy season, the tomato plants are vulnerable to various diseases. A disease that attacks the leaves of tomato plants (foliar diseases) such as late blight (Phytophtora infestans) and spotting bacteria (bacterial spot / Xanthomonas sp.) In addition, there is a disease that attacks the roots such as fusarium and bacterial wilt. If not immediately anticipated, it will decrease the quality and quantity of crop yields. In fact, it can lead to crop failure. The aim of this research is to know the production of tomato grafting by using Timoty and CLN 3024 tomatoes at rain shelter during rainy season in lowland. Data were analyzed using analysis of variance and tested further by Least Significant Difference (LSD) level of 5 %. The parameters measured were plant height (cm), stem diameter (cm), number of fruit space, canopy extended, number of branches, number of productive branches, and the number of stem segments. The results show at the beginning of growth until the end of the treatment without grafting with relative rain shelter displays the highest plant height. This was followed by extensive crop canopy. For tomato grafting and non-grafting using rain shelter able to produce the number of branches and number of productive branches at most. While at the end of the growth in the number of productive branches generated as much. Highest production of tomatoes produced by tomato dig rafting to use the shelter.

Keywords: field trail, wet and dry season, production, diseases, rain shelter

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Authors: Rajani S. Pujar, Pandurangarao N. Kulkarni

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Increased temporal masking affects the speech perception in persons with sensorineural hearing impairment especially under adverse listening conditions. This paper presents a cascaded scheme, which employs a noise reduction algorithm as well as temporal splitting of the speech signal. Earlier investigations have shown that by splitting the speech temporally and presenting alternate segments to the two ears help in reducing the effect of temporal masking. In this technique, the speech signal is processed by two fading functions, complementary to each other, and presented to left and right ears for binaural dichotic presentation. In the present study, half cosine signal is used as a fading function with crossover gain of 6 dB for the perceptual balance of loudness. Temporal splitting is combined with noise reduction algorithm to improve speech perception in the background noise. Two noise reduction schemes, namely spectral subtraction and Wiener filter are used. Listening tests were conducted on six normal-hearing subjects, with sensorineural loss simulated by adding broadband noise to the speech signal at different signal-to-noise ratios (∞, 3, 0, and -3 dB). Objective evaluation using PESQ was also carried out. The MOS score for VCV syllable /asha/ for SNR values of ∞, 3, 0, and -3 dB were 5, 4.46, 4.4 and 4.05 respectively, while the corresponding MOS scores for unprocessed speech were 5, 1.2, 0.9 and 0.65, indicating significant improvement in the perceived speech quality for the proposed scheme compared to the unprocessed speech.

Keywords: MOS, PESQ, spectral subtraction, temporal splitting, wiener filter

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Authors: Sivilai Jayankura

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The objective is to study the behaviors, lifestyles and consumption of the student of Suan Sunandha Rajabhat University. This paper is survey research by using a questionnaire to collect the data with students of Suan Sunandha Rajabhat University for 385 sampling, random coincidence sampling has been provide. Data analysis by descriptive statistics include the distribution, frequency, percentage, average, and standard deviation. The result found that the majority of students are female, and spend their time with their own ideas, like socializing with friends and shopping at the shopping mall, see the movie at the theaters and at the night time will enjoy with their mobile phone and found they long for the quality-price and also brand name regarding the dress. The media and promotion is a key factor impact to the decision to purchase the product and service with mobile phones will be good business to expand business channel also.

Keywords: consumption of teenager, internet, lifestyle behavior, Suan Sunundha Rajabhat University

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Authors: Aleksandra Twarda, Dobrosława Krzemień, Grzegorz Dubin, Tad A. Holak

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Stabilin-2 belongs to the group of scavenger receptors and plays a crucial role in clearance of more than 10 ligands from the bloodstream, including hyaluronic acid, products of degradation of extracellular matrix and metabolic products. The Link domain, a defining feature of stabilin-2, has a sequence similar to Link domains in other hyaluronic acid receptors, such as CD44 or TSG-6, and is responsible for most of ligands binding. Present knowledge of signal transduction by stabilin-2, as well as ligands’ recognition and binding mechanism, is limited. Until now, no experimental structures have been solved for any segments of stabilin-2. It has recently been demonstrated that the stabilin-2 knock-out or blocking of the receptor by an antibody effectively opposes cancer metastasis by elevating the level of circulating hyaluronic acid. Moreover, loss of expression of stabilin-2 in a peri-tumourous liver correlates with increased survival. Solving of the crystal structure of stabilin-2 and elucidation of the binding mechanism of hyaluronic acid could enable the precise characterization of the interactions in the binding site. These results may allow for designing specific small-molecule inhibitors of stabilin-2 that could be used in cancer therapy. To carry out screening for crystallization of stabilin-2, we cloned constructs of the Link domain of various lengths with or without surrounding domains. The folding properties of the constructs were checked by nuclear magnetic resonance (NMR). It is planned to show the binding of hyaluronic acid to the Link domain using several biochemical methods, i.a. NMR, isothermal titration calorimetry and fluorescence polarization assay.

Keywords: stabilin-2, Link domain, X-ray crystallography, NMR, hyaluronic acid, cancer

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Authors: Mona Rezaei, Habib Honari, Mehrzad Hamidi, Fatemeh Kiani

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Make strong brands has become a priority for many organizations in marketing. Brand is an important indicator of marketing status. Brand Strength is in kept customer, profit, brand development and gain competitive advantage and In fact it is a concept that was created from a consumer perspective. It is assumed that the creation of a strong brand is creating numerous marketing benefits. The purpose of this study was to evaluate the psychometric characteristics of the questionnaire the most strong sports brands in the consumer society. Questionnaire was conducted to a sample of 340 customers of sports brands. Psychometric parameters were determined by using appropriate statistical methods. The results of the factor analysis and Varimax rotation revealed five factors of strong brands. The results confirms that questionnaire structure have acceptable associated to the data and confirmed all indicators of the model. Reliability (859/0) was satisfactory. According to calculated psychometric indices, this questionnaire could be appropriate to assess the most strong sports brands.

Keywords: reliability, strong brand, sport brands, psychometric

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Authors: Grichting Anna, Al Sada Sara, Caccayam Angelica, Khan Urshi

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The Qatar Museums Authority recently announced a series of public art initiatives in Doha with the purpose of 'bringing art out of the walls of the museum' to make it accessible to the public on a daily basis and to encourage discussion and debate. While the installation of sculptures in public spaces is not new in Doha, the practice of integrating art in public spaces and architectural projects is reaching a new dimension as internationally renowned artists – such as Damien Hirst and Richard Serra - are being commissioned to install their works in the public spaces and buildings of the city of Doha as well as in more remote desert locations. This research discusses the changing presence, role and context of public art in Doha, both from a historical and cultural overview, and the different forms and media as well as the typologies of urban and public spaces in which the art is installed. It examines the process of implementing site-specific artworks, looking at questions of scale, history, social meaning and formal aesthetics. The methodologies combine theoretical research on the understanding of public art and its role and placement in public space, as well as empirical research on contemporary public art projects in Doha, based on documentation and interviews and as well as site and context analysis of the urban or architectural spaces within which the art is situated. Surveys and interviews – using social media - in different segments of the contemporary Qatari society, including all nationalities and social groups, are used to measure and qualify the impacts and effects on the population.

Keywords: public space, public art, urban design, knowledge economy

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Authors: Xingxing Peng

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With the development of society, there are more and more online communication scenarios such as teleconference and online education. In the process of conference communication, the quality of voice communication is a very important part, and noise may cause the communication effect of participants to be greatly reduced. Therefore, voice noise reduction has an important impact on scenarios such as voice calls. This research focuses on the key technologies of the sound transmission process. The purpose is to maintain the audio quality to the maximum so that the listener can hear clearer and smoother sound. Firstly, to solve the problem that the traditional speech enhancement algorithm is not ideal when dealing with non-stationary noise, an adaptive speech noise reduction algorithm is studied in this paper. Traditional noise estimation methods are mainly used to deal with stationary noise. In this chapter, we study the spectral characteristics of different noise types, especially the characteristics of non-stationary Burst noise, and design a noise estimator module to deal with non-stationary noise. Noise features are extracted from non-speech segments, and the noise estimation module is adjusted in real time according to different noise characteristics. This adaptive algorithm can enhance speech according to different noise characteristics, improve the performance of traditional algorithms to deal with non-stationary noise, so as to achieve better enhancement effect. The experimental results show that the algorithm proposed in this chapter is effective and can better adapt to different types of noise, so as to obtain better speech enhancement effect.

Keywords: speech noise reduction, speech enhancement, self-adaptation, Wiener filter algorithm

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Authors: Subarna Ferdous, Mitsuru Ikeda

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For the shrimp companies to remain relevant to its local and international consumers, they must offer new shrimp product and services. It must work actively not just to create value for the consumer, but to involve the consumer in co-creating value for shrimp product innovation in the market. In this theoretical work, we conceptualize the business concept of value co-creation in the context of shrimp products, and propose a framework of value co-creation for shrimp product innovation in shrimp industries. With guidance on value co-creation in in shrimp industry, and shrimp value chain actors mapped to the co-creation cycle, companies can use the framework to offer new shrimp product to consumer communities. Although customer co-creation is known approach in the world, it is not commonly used by the companies in Bangladesh. This paper makes an original contribution by conceptualizing co-creation and set the examples of best co-creation practices in food sector. The results of the study provide management with guidelines for successful co-creation projects with an innovation- and market-oriented approach. The framework also provides a basis for further research in this area.

Keywords: bangladesh, shrimp industry, value co-creation, shrimp product

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Authors: Chen Bingru

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This study is intended to describe and analyze the effects of polysyllabic shortening and word or phrase boundary on the duration patterns of spoken utterances by Mandarin learners of English in comparison with native speakers of English. To investigate the relative contribution of these effects, two production experiments were conducted. The study included 11 native British English speakers and 20 Mandarin learners of English who were asked to produce four sets of tokens consisting of a mono-syllabic base form, disyllabic, and trisyllabic words derived from the base by the addition of suffixes, and a set of short sentences with a particular combination of phrase size, stress pattern, and boundary location. The duration of words and segments was measured, and results from the data analysis suggest that the amount of polysyllabic shortening and the effect of word or phrase position are likely to affect a Chinese accent for Mandarin ESL speakers. This study sheds light on research on the duration patterns of language by demonstrating the effect of duration-related factors on the foreign accent of Mandarin ESL speakers. It can also benefit both L2 learners and language teachers by increasing their sensitivity to the duration differences and difficulties experienced by L2 learners of English. An understanding of the amount of polysyllabic shortening and the effect of position in words and phrase on syllable duration can also facilitate L2 teachers to establish priorities for teaching pronunciation to ESL learners.

Keywords: duration patterns, Chinese accent, Mandarin ESL speakers, polysyllabic shortening

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Authors: Boussoualim Nacira, Aklouf Youcef

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Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Naira Ghambaryan, Gagik Hakobyan

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Purpose:The study was to evaluate the survival rate of short implants (5-6 mm) functionalized with UV radiation placed in the posterior segments of the atrophied maxilla. Materials and Methods:The study included 47 patients with unilateral/bilateral missing teeth and vertical atrophy of the posterior maxillary area. A total of 64 short UV-functionalized implants and 62 standard implants over 10 mm in length were placed in patients. The clinical indices included the following parameters: ISQБ MBL, OHIP-G scale. Results: For short implants, the median ISQ at placement was 62.2 for primary stability, and the median ISQ at 5 months was 69.6 ISQ. For standart implant, the mean ISQ at placement was 64.3 ISQ, and ISQ after 5 months was 71.6 ISQ. Аfter 6 months mean MBL short implants 0.87 mm, after 1 year, 1.13 mm, after 5 year was 1.48 mm. Аfter 6 months, mean MBL standard implants 0.84 mm, after 1 year, 1.24 mm, after 5 year was 1.58 mm. Mean OHIP-G scores -patients satisfaction with the implant at 4.8 ± 0.3, satisfaction with the operation 4.6 ± 0.4; satisfaction with prosthetics 4.7 ± 0.5. Cumulative 5-year short implants rates was 96.7%, standard implants was 97.4%, and prosthesis cumulative survival rate was 97.2%. Conclusions: Short implants with ultraviolet functionalization for prosthetic rehabilitation of the posterior resorbed maxilla region is a reliable, reasonable alternative to sinus lift, demonstrating fewer complications, satisfactory survival of a 5-year follow-up period, and reducing the number of additional surgical interventions and postoperative complications.

Keywords: short implant, ultraviolet functionalization, atrophic posterior maxilla, prosthodontic rehabilitation

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

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The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Ayman Othman, Tallat Ali

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A pavement maintenance management system (PMMS) was developed for the city of Aswan as a model of a small city to provide the road maintenance department in Aswan city with the capabilities for comprehensive planning of the maintenance activities needed to put the internal pavement network into desired physical condition in view of maintenance budget constraints. The developed system consists of three main stages. First is the inventory & condition survey stage where the internal pavement network of Aswan city was inventoried and its actual conditions were rated in segments of 100 meters length. Second is the analysis stage where pavement condition index (PCI) was calculated and the most appropriate maintenance actions were assigned for each segment. The total maintenance budget was also estimated and a parameter based ranking criteria were developed to prioritize maintenance activities when the available maintenance budget is not sufficient. Finally comes the packaging stage where approved maintenance budget is packed into maintenance projects for field implementation. System results indicate that, the system output maintenance budget is very reasonable and the system output maintenance programs agree to a great extent with the actual maintenance needs of the network. Condition survey of Aswan city road network showed that roughness is the most dominate distress. In general, the road network can be considered in a fairly reasonable condition, however, the developed PMMS needs to be officially adapted to maintain the road network in a desirable condition and to prevent further deterioration.

Keywords: pavement, maintenance, management, system, distresses, survey, ranking

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Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Ala Hanetite

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This study aims to investigate the implications of quality management system (QMS) practices in employees' attitudes relating to job involvement, job satisfaction, career satisfaction, and organizational commitment. Design/methodology/approach: This study was accomplished through the use of a questionnaire. Twenty hypotheses related to QMS practices and the employees' attitudes were formulated and tested. Findings: The results indicate that responsibility and teamwork have a significant and positive correlation with job involvement, job satisfaction, career satisfaction, as well as organizational commitment. Ongoing improvement and problem solving have significant implications in organizational commitment. In addition, training and education, as well as customer focus, did not demonstrate any favorable contribution to the employees' attitudes. Originality/value: The study recommends that management should be more committed to the development of quality practices to sustain and enhance employees' positive attitudes toward their job. Such practices are a competitive strategy to attract and retain competent employees.

Keywords: attitudes, employee, quality management system, competitive strategy

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Stavros T. Ponis, George D. Plakas-Koumadorakis, Sotiris P. Gayialis

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Augmented Reality (AR) can be defined as a technology, which takes the capabilities of computer-generated display, sound, text and effects to enhance the user's real-world experience by overlaying virtual objects into the real world. By doing that, AR is capable of providing a vast array of work support tools, which can significantly increase employee productivity, enhance existing job training programs by making them more realistic and in some cases introduce completely new forms of work and task executions. One of the most promising AR industrial applications, as literature shows, is the use of Head Worn, monocular or binocular Displays (HWD) to support logistics and production operations, such as order picking, part assembly and maintenance. This paper presents the initial results of an ongoing research project for the introduction of a dedicated AR-HWD solution to the picking process of a Distribution Center (DC) in Greece operated by a large Telecommunication Service Provider (TSP). In that context, the proposed research aims to determine whether gamification elements should be integrated in the functional requirements of the AR solution, such as providing points for reaching objectives and creating leaderboards and awards (e.g. badges) for general achievements. Up to now, there is a an ambiguity on the impact of gamification in logistics operations since gamification literature mostly focuses on non-industrial organizational contexts such as education and customer/citizen facing applications, such as tourism and health. To the contrary, the gamification efforts described in this study focus in one of the most labor- intensive and workflow dependent logistics processes, i.e. Customer Order Picking (COP). Although introducing AR in COP, undoubtedly, creates significant opportunities for workload reduction and increased process performance the added value of gamification is far from certain. This paper aims to provide insights on the suitability and usefulness of AR-enhanced gamification in the hard and very demanding environment of a logistics center. In doing so, it will utilize a review of the current state-of-the art regarding gamification of production and logistics processes coupled with the results of questionnaire guided interviews with industry experts, i.e. logisticians, warehouse workers (pickers) and AR software developers. The findings of the proposed research aim to contribute towards a better understanding of AR-enhanced gamification, the organizational change it entails and the consequences it potentially has for all implicated entities in the often highly standardized and structured work required in the logistics setting. The interpretation of these findings will support the decision of logisticians regarding the introduction of gamification in their logistics processes by providing them useful insights and guidelines originating from a real life case study of a large DC operating more than 300 retail outlets in Greece.

Keywords: augmented reality, technology acceptance, warehouse management, vision picking, new forms of work, gamification

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Jayesh M. Patel, Bharat P. Modi

Abstract:

The availability of on mobile devices that can invoke the demonstrated that the total data demand from users is far higher than previously articulated by measurements based solely on a cellular-centric view of smart-phone usage. The ratio of Wi-Fi to cellular traffic varies significantly between countries, This paper is shown the compression between the cellular data usage and Wi-Fi data usage by the user. This strategy helps operators to understand the growing importance and application of yield management strategies designed to squeeze maximum returns from their investments into the networks and devices that enable the mobile data ecosystem. The transition from unlimited data plans towards tiered pricing and, in the future, towards more value-centric pricing offers significant revenue upside potential for mobile operators, but, without a complete insight into all aspects of smartphone customer behavior, operators will unlikely be able to capture the maximum return from this billion-dollar market opportunity.

Keywords: cellular, Wi-Fi, mobile, smart phone

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Authors: Kajal Zarei

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Supply chain management is becoming an increasingly important issue in many businesses today. In such circumstances, a number of reasons such as management deficiency in different segments of the supply chain, lack of streamlined processes, resistance to change the current systems and technologies, and lack of advanced information system have paved the ground to ask for innovative research studies. To this end, information technology (IT) is becoming a major driver to overcome the supply chain limitations and deficiencies. The emergence of IT has provided an excellent opportunity for redefining the supply chain to be more effective and competitive. This paper has investigated the IT impact on two-digit industry codes in the International Standard Industrial Classification (ISIC) that are operating in four groups of the supply chains. Firstly, the primary fields of the supply chain were investigated, and then paired comparisons of different industry parts were accomplished. Using experts' ideas and Analytical Hierarchy Process (AHP), the status of industrial activities in Kurdistan Province in Iran was determined. The results revealed that manufacturing and inventory fields have been more important compared to other fields of the supply chain. In addition, IT has had greater impact on food and beverage industry, chemical industry, wood industry, wood products, and production of basic metals. The results indicated the need to IT awareness in supply chain management; in other words, IT applications needed to be developed for the identified industries.

Keywords: supply chain, information technology, analytical hierarchy process, two-digit codes, international standard industrial classification

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Authors: Marc Dorval, Marie-Hélène Jobin

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This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough search into their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, attributes, satisfaction and meeting or exceeding customer expectations), whereas in HCS, two approaches are prominent (Donabedian’s structure, process and outcomes model and Lohr and Schroeder’s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. This work then proposes an encompassing definition of quality as a lever and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.

Keywords: healthcare, management, operations, quality, services

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Authors: Sukhwinder K. Bhullar, M. B. G. Jun

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The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

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Authors: Hala A. Alrumaih

Abstract:

It is widely believed that mobile device is a promising technology for lending the opportunity for the third wave of electronic commerce. Mobile devices have changed the way companies do business. Many applications are under development or being incorporated into business processes. In this day, mobile applications are a vital component of any industry strategy. One of the greatest benefits of selling merchandise and providing services on a mobile application is that it widens a company’s customer base significantly. Mobile applications are accessible to interested customers across regional and international borders in different electronic business (e-business) area. But there is a dark side to this success story. The security risks associated with mobile devices and applications are very significant. This paper introduces a broad risk analysis for the various threats, vulnerabilities, and risks in mobile e-business applications and presents some important risk mitigation approaches. It reviews and compares two different frameworks for security assurance in mobile e-business applications. Based on the comparison, the paper suggests some recommendations for applications developers and business owners in mobile e-business application development process.

Keywords: e-business, mobile applications, risk mitigations, security assurance

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Authors: Hokuma Isgandarova, Khalil Aryanfar

Abstract:

The patient's rights include all care items that the patient has the right to receive. Considering the growing importance of this important issue and its effect on improving treatment results and customer satisfaction, the present study was conducted with the aim of investigating the level of respect for patient rights in the physiotherapy clinic of the Faculty of Medicine University of Medical Sciences in 2023. In this study, the patients or companions who were referred to the clinic answered questions about the performance status of the clinic with respect to various aspects of the patient's rights. The aspects that were studied: choosing the service provider, having authority, respect, safety, prevention and access were found to have inappropriate performance scores. However, communication and interaction, continuity of service, quality of basic facilities and facilities, timely and immediate attention and trust had appropriate performance. Also, the results of the data analysis showed that there is no significant relationship between the total performance score and any of the demographic variables.

Keywords: compliance, patients' rights, physiotherapy clinic, performance level

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