Search results for: resource curse hypothesis

Authors: Manojkumar Sabanayagam

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The Riemann hypothesis is an unsolved millennium problem and the search for a solution to the Riemann hypothesis is to study the pattern of prime number distribution. The scope of this paper is to identify the solution for the critical strip and the critical line axis, which has the non-trivial zero solutions using complex plane functions. The Riemann graphical plot is constructed using a linear complex variable function (X+iY) and is applicable only when X>1. But the investigation shows that complex variable behavior has two zones. The first zone is the transformation zone, where the definition of the complex plane should be a non-linear variable which is the critical strip zone in the graph (X=0 to 1). The second zone is the transformed zone (X>1) defined using linear variables conventionally. This paper deals with the Non-linear function in the transformation zone derived using cosine and sinusoidal time lag w.r.t imaginary number ‘i’. The alternate complex variable (Cosθ+i Sinθ) is used to understand the variables in the critical strip zone. It is concluded that the non-trivial zeros present in the Real part 0.5 are because the linear function is not the correct approach in the critical strip. This paper provides the solution to Reimann's hypothesis.

Keywords: Reimann hypothesis, critical strip, complex plane, transformation zone

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Authors: Indu Saini, Ashu Khanna, S. K. Peddoju

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Cloud computing is the new buzz word today attracting high interest among various domains like business enterprises, Particularly in Small and Medium Enterprises. As it is a pay-per-use model, SMEs have high expectations that adapting this model will not only make them flexible, hassle-free but also economic. In view of such expectations, this paper analyses the possibility of adapting cloud computing technologies in SMEs in light of economic concerns. In this paper, two hypotheses are developed to compare the average annual per-user costs of using Enterprise Resource Planning systems in two ways, The traditional approach and the cloud approach. A web based survey is conducted apart from the Interviews with the peers to collect the data across the selected SMEs and t-test is performed to compare both the technologies on the proposed hypothesis. Results achieved are produced and discussed.

Keywords: cloud computing, small and medium enterprises, enterprise resource solutions, interviews

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Atiq Zaman

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The high contamination rate in the recycling waste stream is one of the major problems in Australia. In addition, a lack of reliable waste data makes it even more difficult for designing and implementing an effective waste management plan. This article conceptualizes the opportunity to improve resource productivity by integrating smart resource tracking system (SRTS) into the Australian household waste management system. The application of the smart resource tracking system will be implemented through the following ways: (i) mobile application-based resource tracking system used to measure the household’s material flow; (ii) RFID, smart image and weighing system used to track waste generation, recycling and contamination; (iii) informing and motivating manufacturer and retailers to improve their problematic products’ packaging; and (iv) ensure quality and reliable data through open-sourced cloud data for public use. The smart mobile application, imaging, radio-frequency identification (RFID) and weighing technologies are not new, but the very straightforward idea of using these technologies in the household resource consumption, waste bins and collection trucks will open up a new era of accurately measuring and effectively managing our waste. The idea will bring the most urgently needed reliable, data and clarity on household consumption, recycling behaviour and waste management practices in the context of available local infrastructure and policies. Therefore, the findings of this study would be very important for decision makers to improve resource productivity in the waste industry by using smart resource tracking system.

Keywords: smart devices, mobile application, smart sensors, resource tracking, waste management, resource productivity

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Authors: R. Maalej, I. Amami, S. Saadaoui

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Within the growing body of literature on corporate entrepreneurship, there is a need to understand the relationship between human resource management and corporate entrepreneurship. This paper outlines the linkage between human resource management practices with corporate entrepreneurship. In response, we propose a review of the literature that is based on a conceptual reading of corporate entrepreneurship, human resource management practices and the relationship between them.

Keywords: human resource management, human resources management practices, corporate entrepreneurship, entrepreneur

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Authors: Yousef Rostami Gharainy

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This paper presents resource consumption accounting as an imaginative way to deal with management accounting which concentrates on administrators as the essential clients of the data and gives the best information of conventional management accounting. This system underscores that association's asset reasons costs, accordingly in costing frameworks the emphasis ought to be on assets and utilization of them. Resource consumption accounting consolidates two costing methodologies, action based and German cost accounting method known as GPK. This methodology notwithstanding giving a chance to managers to decide, makes task management accounting as operational. The reason for this article is to clarify the idea of resource consumption accounting, its parts and highlights and use of this strategy in associations. In the first place we deliver to presentation of resource consumption accounting, foundation, reasons for its development and the issues that past costing frameworks confronted it. At that point we give standards and presumptions of this technique; at last we depict the execution of this strategy in associations and its preferences over other costing strategies.

Keywords: resource consumption accounting, management accounting, action based method, German cost accounting method

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Authors: Ploychompoo Kittikunchotiwut

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This study examines the relationships between human resource practices, knowledge management capacity, and innovation performance. The data were collected by using a questionnaire from 241 firms in the hotels in Thailand. The hypothesized relationships among variables are examined by using ordinary least square (OLS) regression analysis. The findings show that human resource practices have a positive effect on knowledge management capacity. Besides, knowledge management capacity was found to positively affect innovation performance. Finally, the limitations of the study and directions for future research are discussed.

Keywords: human resource practices, knowledge management capacity, innovation performance

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Authors: Nana Weng

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Firstly, based on two diamond models and Value-Rarity-Inimitability-Organization framework, this paper analyzes the Country Specific factors of and firm specific factors which influence subsidiaries’ sustainable competitive advantage. Then, according to the main content of Strategic Human Resource Management (SHRM) research that HRM strategy should fit into corporate strategy, we explained what the SHRM practices should be in the context of localization strategies within Multinational Enterprise (MNE) companies. Then we choose two Japanese MNE subsidiaries in the same industry and tested the hypothesis that localization SHRM practices positively impact on subsidiary’s sustainable competitive advantage, further positively affect firm integrated performance (both financial performance and organizational and organizational performance) lever through High Performance Work Practices (HPWPs) of local employees.

Keywords: localization SHRM, firm integrated performance, Japanese MNE subsidiaries, Vietnam

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Sarah Majid Ansari, Serjosha Wulf, Matthias Goerke

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In times of global warming and the increasing shortage of resources, sustainable production is becoming more and more inevitable. Companies cannot only heighten their competitiveness but also contribute positively to environmental protection through efficient energy and resource consumption. Regarding this, technical solutions are often preferred during production, although organizational and process-related approaches also offer great potential. This project focuses on reducing resource usage, with a special emphasis on the human factor. It is the aspiration to develop a methodology that systematically implements and embeds suitable and individual measures and methods regarding resource efficiency throughout the entire production. The measures and methods established help employees handle resources and energy more sensitively. With this in mind, this paper also deals with the difficulties that can occur during the sensitization of employees and the implementation of these measures and methods. In addition, recommendations are given on how to avoid such difficulties.

Keywords: implementation, human factors, production plants, resource efficiency

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Darshana Lal, Sonu Rana

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Learning Resource Centers (LRC) are acquiring different kinds of documents like books, journals, thesis, dissertations, standard, databases etc. in print and e-form. This article deals with the different types of sources available in LRC. It also discusses the concept of the web, as a tool, as a multimedia system and the different interfaces available on the web. The reasons for establishing LRC are highlighted along with the assignments of LRC. Different features of LRC‘S like self-learning and group learning are described. It also implements a group of activities like reading, learning, educational etc. The use of LRC by students and faculties are given and concluded with the benefits.

Keywords: internet, search engine, resource centre, opac, self-learning, group learning

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Authors: Boyun Lee

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This study aims to discuss whether anthropomorphism some scientists tend to use in cross-species comparison can be justified epistemologically, especially in the primate mind-reading debate. Concretely, this study critically analyzes Elliott Sober’s argument about mind-reading hypothesis (MRH), an anthropomorphic hypothesis which states that nonhuman primates (e.g., chimpanzee) are mind-readers like humans. Although many scientists consider anthropomorphism as an error and choosing anthropomorphic hypothesis like MRH without any definite evidence invalid, Sober advocates that anthropomorphism is supported by cladistic parsimony that suggests choosing the simplest hypothesis postulating the minimum number of evolutionary changes, which can be justified epistemologically in the mind-reading debate. However, his argument has several problems. First, Reichenbach’s theorem which Sober uses in process of showing that MRH has the higher likelihood than its competing hypothesis, behavior-reading hypothesis (BRH), does not fit in the context of inferring the evolutionary relationship. Second, the phylogenetic tree Sober supports is one of the possible scenarios of MRH, and even without this problem, it is difficult to prove that the possibility nonhuman primate species and human share mind-reading ability is higher than the possibility of the other case, considering how evolution occurs. Consequently, it seems hard to justify anthropomorphism of MRH under Sober’s argument. Some scientists and philosophers say that anthropomorphism sometimes helps observe interesting phenomena or make hypotheses in comparative biology. Nonetheless, we cannot determine that it provides answers about why and how the interesting phenomena appear or which of the hypotheses is better, at least the mind-reading debate, under the current state.

Keywords: anthropomorphism, cladistic parsimony, comparative biology, mind-reading debate

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Authors: Jucelia Appio, Danielle Deimling De Carli, Bruno Henrique Rocha Fernandes, Nelson Natalino Frizon

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The purpose of this paper is to investigate if there are positive and significant correlations between the dimensions of Person-Environment Fit (Person-Job, Person-Organization, Person-Group and Person-Supervisor) at the “Best Companies to Work for” in Brazil in 2017. For that, a quantitative approach was used with a descriptive method being defined as a research sample the "150 Best Companies to Work for", according to data base collected in 2017 and provided by Fundação Instituto of Administração (FIA) of the University of São Paulo (USP). About the data analysis procedures, asymmetry and kurtosis, factorial analysis, Kaiser-Meyer-Olkin (KMO) tests, Bartlett sphericity and Cronbach's alpha were used for the 69 research variables, and as a statistical technique for the purpose of analyzing the hypothesis, Pearson's correlation analysis was performed. As a main result, we highlight that there was a positive and significant correlation between the dimensions of Person-Environment Fit, corroborating the H1 hypothesis that there is a positive and significant correlation between Person-Job Fit, Person-Organization Fit, Person-Group Fit and Person-Supervisor Fit.

Keywords: Human Resource Management (HRM), Person-Environment Fit (PE), strategic people management, best companies to work for

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Chris George, Adam Hamlin, Lily Pereg, Richard Charlesworth, Gal Winter

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Background: According to the ‘hygiene hypothesis’ the current rise in allergies and autoimmune diseases stems mainly from reduced microbial exposure due, amongst other factors, to urbanisation and distance from soil. However, this hypothesis is based on epidemiological and not biological data. Useful insights into the underlying mechanisms of this hypothesis can be gained by studying our interaction with soil. Soil microbiota may be directly ingested or inhaled by humans, enter the body through skin-soil contact or using plants as vectors. This study aims to examine the ability of soil microbiota to colonise the gut, study the interaction of soil microbes with the immune system and their potential protective activity. Method: The nutrition of the rats was supplemented daily with fresh or autoclaved soil for 21 days followed by 14 days of no supplementations. Faecal samples were collected throughout and analysed using 16S sequencing. At the end of the experiment rats were sacrificed and tissues and digesta were collected. Results/Conclusion: Results showed significantly higher richness and diversity following soil supplementation even after recovery. Specific soil microbial groups identified as able to colonise the gut. Of particular interest was the mucosal layer which emerged as a receptive host for soil microorganisms. Histological examination revealed innate and adaptive immune activation. Findings of this study reinforce the ‘hygiene hypothesis’ by demonstrating the ability of soil microbes to colonise the gut and activate the immune system. This paves the way for further studies aimed to examine the interaction of soil microorganisms with the immune system.

Keywords: gut microbiota, hygiene hypothesis, microbiome, soil

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Authors: Mohammad Sarchami, Mohsen Zeinalkhani

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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.

Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm

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Authors: T. O. Adekunle, R. L. Makhubu, C. N. Ngwane

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This research was designed to assess the validity of the Sapir Whorf hypothesis in relation to the linguistic and cultural notions of the Yoruba and Zulu language speakers’ via the evaluation of the culture enriched dramatic text The Lion and The Jewel by Wole Soyinka. The study queried both the hypothesis’ strong version, (language governs thought: linguistic classifications restrain and influence mental classifications); and its weak version, (linguistic classifications and their use influence thought as well as some other classes of non-linguistic activities) and their possible reliability. Participants were purposively selected and their ages ranged from 16-46 years old. The participants amounted to 38 (18 Yoruba and 20 Zulu) students of DUT who all speak both English and Zulu (Zulu participants) and English and Yoruba (Yoruba participants) and the mixed methods approach was used. Thus with the use of questionnaire and interviews the research questions were answered and the findings provided support for validity of the linguistic relativity hypothesis, languages indeed influence thought. The findings also revealed that linguistic influence on cognition is not limited to different language users alone, but also same language speakers per level of exposure to other languages and concepts.

Keywords: culture, cognition, DUT, language, linguistic relativity hypothesis, Sapir-Whorf hypothesis, The Lion and The Jewel, thought, Wole Soyinka, Yoruba, Zulu

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Authors: Shaban Guma, Naim Bajcinca

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We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

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Authors: Yashvi Italiya

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Dysthymia (DD) is a much-overlooked soft mood disorder and mostly confused with other forms of chronic depression. This research paper gives a spotlight to the DD prevailing in men and women. It also focuses on one of the comorbidities of Dysthymia, i.e., Anxiety. The comorbidities, hurdles in diagnosis, the ubiquity of the disorder, and the relation of Anxiety and DD are briefly described. Gender was the main focus here because the researcher of this paper found it as a research gap while doing the literature review. The study was done through secondary data obtained primarily from a questionnaire having Alpha 0.891 reliability. T-test method of data analysis was used to test the hypotheses. The result shows that the researcher failed to accept alternative hypothesis 1 (M1 > M2), while the alternative hypothesis 2 (M1 > M2) was accepted. The ratio of DD in women (M1) is not higher than that of men (M2) (hypothesis 1). But, women are more anxious than men (hypothesis 2). It was found that comorbid Anxiety is more widespread in one gender. It further plays a significant role in mixing up the symptoms. It was concluded that the dividing line between Dysthymia and MDD is still unclear for an accurate diagnosis. There is an essential need for spreading knowledge concerning the differences between the symptoms of DD and MDD so that the actual disorder can be identified, and proper help can be received from/provided by professionals.

Keywords: anxiety, comorbidity, dysthymia, gender, MDD

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Authors: Lorraine Joyce Chua, Sheena Fatima Ragas, Flora Mae Tantay, Carolyn Marie Sunio

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The Philippines is one of the countries most affected by weather-related disasters. The occurrence of natural disasters in this country increases due to environmental degradation making environment preservation a growing trend in the society including the corporate world. Most organizations implemented green practices in order to lower expenses unaware that some of these practices were already a part of a new trend in human resource management known as Green Human Resource Management (GHRM). GHRM is when business organizations implement HR policies programs processes and techniques that bring environmental impact and sustainability practices on the organization. In relation to this, the study hypothesizes that implementing GHRM practices in the workplace will spillover to an employees lifestyle and such lifestyle may moderate the impact of GHRM practices to his job performance. Private industries located in the Philippines National Capital Region (NCR) were purposively selected for the purpose of this study. They must be ISO14001 certified or are currently aiming for such certification. The employee respondents were randomly selected and were asked to answer a reliable and valid researcher-made questionnaire. Structural equation modeling (SEM) supported the hypothesis that GHRM practices may spillover to employees lifestyle stimulating such individual to start a green lifestyle which moderates the impact of GHRM to his job performance. It can also be implied that GHRM practices help shape employees to become environmentally aware and responsible which may help them in preserving the environment. The findings of this study may encourage Human Resource practitioners to implement GHRM practices in the workplace in order to take part in sustaining the environment while maintaining or improving employees job performance and keeping them motivated. This study can serve as a basis for future research regarding the importance of strengthening the GHRM implementation here in the Philippines. Future studies may focus more on the impact of GHRM to other factors, such as job loyalty and job satisfaction of the employees belonging to specific industries which would greatly contribute to the GHRM community in the Philippines.

Keywords: GHRM practices, Green Human Resource Management, Green Lifestyle, ISO14001, job performance, Philippines

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Authors: R. Gupta, P. Jain, S. Das

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One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

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Authors: Aamar Ilyas

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Value of firm does not only depend upon its financial and material resources rather human resource is also a significant contributor in success of organizations by achieving competitive advantage. Human resource is an important asset so it is the main responsibility of employers to get the best use of this resource. Hence, this paper will explore the human resource practices used by entrepreneurs in the informal economy in Lahore, the provincial capital of Punjab, Pakistan. In this study three major sectors are randomly selected. Snowball sampling technique was applied to collect data. Survey was conducted through interviews of 45 respondents working in the informal sector. The results show that informal sector in Pakistan is not using any formal human resource practices as done by formal enterprises. Findings suggest that there should be the implementation of the human resource practices that help the firm to increase its productivity and ensure the betterment of the employees. The main limitation of the study was short time period to cater all sectors of informal economy of Pakistan which limits the extent of its generalizability. The rationale behind this study is to uncover the facts regarding management practices of human capital in the informal sector.

Keywords: HR practices, informal economy, working condition, recruitment, training, employee motivation, welfare

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Authors: Anastasios Ntousas

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The purpose of the following paper is to analyze the relationship between the lexical quality and the self-teaching hypothesis and their impact on the reading ability. The following questions emerged, is there a correlation between the effective reading experience that the lexical quality hypothesis proposes and the self-teaching hypothesis, would the ability to read by analogy facilitate and create stable, synchronized four-word representational, and would word morphological knowledge be a possible extension of the self-teaching hypothesis. The lexical quality hypothesis speculates that words include four representational attributes, phonology, orthography, morpho-syntax, and meaning. Those four-word representations work together to make word reading an effective task. A possible lack of knowledge in one of the representations might disrupt reading comprehension. The degree that the four-word features connect together makes high and low lexical word quality representations. When the four-word representational attributes connect together effectively, readers have a high lexical quality of words; however, when they hardly have a strong connection with each other, readers have a low lexical quality of words. Furthermore, the self-teaching hypothesis proposes that phonological recoding enables printed word learning. Phonological knowledge and reading experience facilitate the acquisition and consolidation of specific-word orthographies. The reading experience is related to strong reading comprehension. The more readers have contact with texts, the better readers they become. Therefore, their phonological knowledge, as the self-teaching hypothesis suggests, might have a facilitative impact on the consolidation of the orthographical, morphological-syntax and meaning representations of unknown words. The phonology of known words might activate effectively the rest of the representational features of words. Readers use their existing phonological knowledge of similarly spelt words to pronounce unknown words; a possible transference of this ability to read by analogy will appear with readers’ morphological knowledge. Morphemes might facilitate readers’ ability to pronounce and spell new unknown words in which they do not have lexical access. Readers will encounter unknown words with similarly phonemes and morphemes but with different meanings. Knowledge of phonology and morphology might support and increase reading comprehension. There was a careful selection, discussion of theoretical material and comparison of the two existing theories. Evidence shows that morphological knowledge improves reading ability and comprehension, so morphological knowledge might be a possible extension of the self-teaching hypothesis, the fundamental skill to read by analogy can be implemented to the consolidation of word – specific orthographies via readers’ morphological knowledge, and there is a positive correlation between effective reading experience and self-teaching hypothesis.

Keywords: morphology, orthography, reading ability, reading comprehension

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Authors: Terence Maisah Seka

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This paper examines democratic governance within the private and public sectors in economies in transition (Cameroon) by exploring how they influence development in terms of resource allocation to priorities that are locally conceptualized. The benefit of this is an improvement in indigenous and the quality of life for the local population. Using an ethnographic approach, this paper suggests that institutional corruption and state bureaucracy has limited the impact of democratic governance in influencing development. This has seen funds for developments being embezzled; local projects are not being done to satisfaction among others. The paper contributes by proposing measures to eliminate corruption to improve democratic governance, which will improve resource allocation and utilization.

Keywords: democratic governance, resource allocation, utilisation, Cameroon

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Authors: Shahna K. C., Belay Menon, Taniya Joshua

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As globalization in the era progresses, spatial inequality is turned to be one of the major concerns; the main intent of the Study is to focus on if there is any interdependencies of culture economy and resource availability on creating spatial inequality in cities. The paper tries to establish the relationship between spatial inequality – the quality of life – the DETERMINANT TRIAD (culture, economy, resource availability). Slum area of Dharavi is taken to evaluate the influence of these determinants on the quality of life as spatial inequality is evident there. Interdependencies of the determinants on creating spatial inequality is evaluated. For this, It is understood that these three parameters, i.e., culture, economy, resource availability, are determinants of urban design, each from the social, economic, environmental domains of sustainability, respectively. And there are studies individually on each of these aspects, how they determine the urban spaces, and how influential on the whole process of urbanization. Now extending the study towards the interdependencies of these three so as to find out how these trilogy shapes the urban form and space.

Keywords: spatial inequality, culture, economy, resource availability, quality of life

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Authors: Itumeleng Judith Maome, Robert Walter Dumisani Zondo

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The concept of Corporate Social Responsibility (CSR) has gained popularity as a management philosophy in companies. They integrate social and environmental concerns into their operations and interactions with stakeholders. While CSR has mostly been associated with large organisations, it contributes to societal goals by engaging in activities or supporting volunteering or ethically oriented practices. However, small and medium enterprises (SMEs) have been recognised for their contributions to the social and economic development of any country. Consequently, this study examines the effect of CSR practices on human resource performance in the selected manufacturing SME in South Africa. This study was quantitative in design and examined the production and related experiences of the manufacturing SME organisation that had adopted a CSR strategy for human resource improvement. The study was achieved by collecting pre- and post-quarterly data, overtime, for employee turnover and labour absenteeism for analysis using the regression model. The results indicate that both employee turnover and labour absenteeism have no relationship with human resource performance post-CSR implementation. However, CSR has a relationship with human resource performance. Any increase in CSR activities results in an increase in human resource performance.

Keywords: corporate social responsibility, employee turnover, human resource, labour absenteeism, manufacturing SME

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Authors: Eli Maikoto Agison

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The relevance of enhancing human resource development in entrepreneurship for economic growth and development cannot be overemphasized since no country can grow and developed economically above its citizenry. Africa for example and Nigeria in particular is lagging behind in terms of economic growth and development when compared with other developed countries of the world like China, Japan, Singapore, USA etc. The reason is not farfetched from these developed countries efforts in enhancing human resource development in entrepreneurship education. For Nigeria to attain this height of development, this paper discusses the meaning of human resource development in entrepreneurship as the framework for helping employees develop their personal and organizational skills knowledge and abilities as this includes employee training, career development and performance management to enable an organization achieve a set goal. While entrepreneurship education is seen as an aspect of education that is geared towards self-reliance, some of the challenges faced in the enhancement of human resource development in Nigeria include inadequate training and re-training of instructors of entrepreneurship in higher education. Insufficient funding to higher education were discussed and recommendations to include adequate funding, training and re-training of instructors of higher education be enhanced as some of the ways forward.

Keywords: economic development, economic growth, entrepreneurship education, human resource development

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Authors: Wei Yaming

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Objective: In order to compare the stress of employees sent overseas with (GRAS) before and after, we used the resource-oriented music listening intervention in this study. We also collected pertinent experimental data. Methods: The experiment involved 47 employees who were sent abroad by the Chinese side. They completed the stress scale test and documented it before the intervention. They tested for stress after five interventions and performed one-on-one interviews. Quantitative data and SPSS software were used to analyze relationships between stress reduction and resource-oriented music listening, as well as Pearson's correlation, multiple regression levels, and ANOVA. For the qualitative analysis, content analysis of one-on-one interviews was performed. Results: A comparison of data from before and after demonstrates how resource-focused music listening activities can lessen and relieve stress in remote workers. In the qualitative study, stress is broken down into six categories: relationship stress, health stress, emotional stress, and frustration stress. External pressures include work pressure and cultural stress. And it has been determined that listening to music that is resource-oriented can better ease internal stress (health, emotion, and dissatisfaction). Conclusion: The Guide Resource-oriented Music Listening (GROML) Program appears to have had some effect on the participants' stress levels. The resources that the participants encountered while listening to music are bravery, calm, letting go, and relaxing.

Keywords: resource-oriented, music listening, oversea dispatch employees, work stress

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Authors: Szymon Rutkowski, Tomasz Korbak

Abstract:

We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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