This study investigates the relationship between mental health and emotional intelligence among senior high school students in a public school. Thus, the study employed a correlational design to measure the relationship between mental health and emotional intelligence among 152 Grade 12 senior high school students in a public school. Hence, to measure the study’s variables - Mental Health Inventory and Emotional Intelligence Scale (EIS) were utilized. Based on the inferential statistics, the r coefficient of 0.32 indicates a low positive correlation (...) between the variables and a p-value of 0.00, indicating a significant relationship between the respondents' mental health and emotional intelligence. Implications and recommendations were discussed in the study. (shrink)

Building on findings that self-uncertainty motivates attempts to restore certainty about the self, particularly in ways that highlight one’s distinctiveness from others, we show that self-uncertainty, relative to uncertainty in general, increases creative generation among individualists. In Studies 1 to 3, high (but not low) individualists performed better on a creative generation task after being primed with self-uncertainty as opposed to general uncertainty. In Study 4, this effect emerged only among those who were told that the task measured creative as (...) opposed to analytical thinking, suggesting that the positive effects of self-uncertainty on performance are specific to tasks that bolster perceptions of uniqueness. In Study 5, self-uncertain individualists experienced a restoration of self-clarity after being induced to think about themselves as more (vs. less) creative. Implications for compensatory responses to self-uncertainty and factors that influence creativity are discussed. (shrink)

ABSTRACT In ‘Scorekeeping in a Pornographic Language Game’, Rae Langton and Caroline West borrow ideas from David Lewis to attempt to explain how pornography might subordinate and silence women. Pornography is supposed to express certain misogynistic claims implicitly, through presupposition, and to convey them indirectly, through accommodation. I argue that the appeal to accommodation cannot do the sort of work Langton and West want it to do: Their case rests upon an overly simplified model of that phenomenon. I argue further (...) that, once we are clear about why Langton and West's account fails, a different and more plausible account of pornography's influence emerges. (shrink)

A speculative investigation of how Frege's logical views change between Begriffsschrift and Grundgesetze and how this might have affected the formal development of logicism.

We attempt here to trace the evolution of Frege’s thought about truth. What most frames the way we approach the problem is a recognition that hardly any of Frege’s most familiar claims about truth appear in his earliest work. We argue that Frege’s mature views about truth emerge from a fundamental re-thinking of the nature of logic instigated, in large part, by a sustained engagement with the work of George Boole and his followers, after the publication of Begriffsschrift and the (...) appearance of critical reviews by members of the Boolean school. (shrink)

This study examined the effectiveness of video-based instruction (VBI) as a learning remediation strategy in teaching Laws of Thermodynamics among Prospective Science Teachers at Bulacan State University. The researchers employed – a one-group pretest–posttest design to assess the 35 prospective science teachers who were purposively selected. More so, data was gathered through researcher-made pretest-posttest achievement tests and an adapted Likert survey questionnaire. The data was treated descriptively and inferentially. The findings showed that VBI as a learning remediation strategy positively affected (...) the preservice teachers’ achievement. In addition, data shows a significant difference between the pretest and posttest in teaching the laws of thermodynamics. The ease of use of VBI as learning remediation in teaching laws of thermodynamics in terms of pedagogical content, individual learning focus, ability to work at pace, and increased engagement was very effective. The learning achievement of the prospective science teachers was significantly related to the ease of use of VBI as a learning remediation. However, it was observed to have a high positive association. Future use of VBI can enhance the prospective science teacher’s competence in using VBI in teaching science subjects. (shrink)

Rae Langton and Caroline West argue that pornography silences women by presupposing misogynistic attitudes, such as that women enjoy being raped. More precisely, they claim that a somewhat infamous pictorial, ‘Dirty Pool’, makes such presuppositions, and that it is typical in this respect. I argue for four claims. (1) There are empirical reasons to doubt that women are silenced in the way that Langton and West claim they are. (2) There is no evidence that very much pornography makes the sorts (...) of presuppositions that Langton and West's explanation of silencing requires it to make. (3) Even ‘Dirty Pool’, for all its other problems, does not make such presuppositions. (4) Langton and West misread ‘Dirty Pool’ because they do not take proper account of the fact that pornography often traffics in sexual fantasy. The broader lesson is that we need to read pornography more sensitively if we are to understand its capacity to shape socio‐sexual norms (for good or for ill). (shrink)

An overview of what Frege accomplishes in Part II of Grundgesetze, which contains proofs of axioms for arithmetic and several additional results concerning the finite, the infinite, and the relationship between these notions. One might think of this paper as an extremely compressed form of Part II of my book Reading Frege's Grundgesetze.

In two recent papers, Bob Hale has attempted to free second-order logic of the 'staggering existential assumptions' with which Quine famously attempted to saddle it. I argue, first, that the ontological issue is at best secondary: the crucial issue about second-order logic, at least for a neo-logicist, is epistemological. I then argue that neither Crispin Wright's attempt to characterize a `neutralist' conception of quantification that is wholly independent of existential commitment, nor Hale's attempt to characterize the second-order domain in terms (...) of definability, can serve a neo-logicist's purposes. The problem, in both cases, is similar: neither Wright nor Hale is sufficiently sensitive to the demands that impredicativity imposes. Finally, I defend my own earlier attempt to finesse this issue, in "A Logic for Frege's Theorem", from Hale's criticisms. (shrink)

This is a completely informal presentation of the ideas behind the diagonal lemma. One really can't see this important result from too many different angles. This one aims at getting the main idea across. (For the cognoscenti, it is in the spirit of Quine's treatment in terms of "appended to its own quotation".).

Disquotationalism is the view that the only notion of truth we really need is one that can be wholly explained in terms of such trivialities as: “Snow is white” is true iff snow is white. The 'Classical Disquotational Strategy' attempts to establish this view case by case, by showing that each extant appeal to truth, in philosophical or scientific explanations, can be unmasked as an appeal only to disquotational truth. I argue here that the Classical Strategy fails in at least (...) two cases: attributions of truth to context-dependent utterances and uses of truth psychological explanations of behavioral success or, more fundamentally, appeals to falsity in psychological explanations of behavioral failure. -/- It's my intention to turn this paper into two papers. It's become quite unwieldy as it is---not unlike "The Strength of Truth Theories". (shrink)

In both the paper "Revisability and Conceptual Change in 'Two Dogmas of Empiricism'" and in Constructing the World, David Chalmers has argued against W.V.O. Quine's claim that there are no 'analytic' sentences. I argue here that Chalmers's argument does not advance this debate.

This brief reply to Ferzan shows that her recent review of Self-Defense, Necessity, and Punishment is incoherent and completely misrepresents a central claim of mine (to the point of attributing to me the opposite claim than the one I am actually and quite clearly and explicitly making). Her other criticisms fall flat too.

Neo-Fregean logicists claim that Hume’s Principle (HP) may be taken as an implicit definition of cardinal number, true simply by fiat. A long-standing problem for neo-Fregean logicism is that HP is not deductively conservative over pure axiomatic second-order logic. This seems to preclude HP from being true by fiat. In this paper, we study Richard Kimberly Heck’s Two-Sorted Frege Arithmetic (2FA), a variation on HP which has been thought to be deductively conservative over second-order logic. We show that it (...) isn’t. In fact, 2FA is not conservative over n-th order logic, for all $n \geq 2$. It follows that in the usual one-sorted setting, HP is not deductively Field-conservative over second- or higher-order logic. (shrink)

How do we acquire the notions of cardinality and cardinal number? In the (neo-)Fregean approach, they are derived from the notion of equinumerosity. According to some alternative approaches, defended and developed by Husserl and Parsons among others, the order of explanation is reversed: equinumerosity is explained in terms of cardinality, which, in turn, is explained in terms of our ordinary practices of counting. In their paper, ‘Cardinality, Counting, and Equinumerosity’, Richard Kimberly Heck proposes that instead of equinumerosity or counting, (...) cardinality is derived from a cognitively earlier notion of _just as many_. In this paper, we assess Heck’s proposal in terms of contemporary theories of number concept acquisition. Focusing on bootstrapping theories, we argue that there is no evidence that the notion of _just as many_ is cognitively primary. Furthermore, since the acquisition of cardinality is an enculturated process, the cognitive primariness of these notions, possibly including _just as many_, depends on various external cultural factors. Therefore, being possibly a cultural construction, _just as many_ could be one among several notions used in the acquisition of cardinality and cardinal number concepts. This paper thus challenges those accounts which seek for a fundamental concept underlying all aspects of numerical cognition. (shrink)

​I evaluate a suggestion, floated by Kimberly Ferzan (this volume), that the twitter hashtag campaign #BelieveWomen is best accommodated by non-reductionist views of testimonial justification. I argue that the issue is ultimately one about the ethical obligation to trust women, rather than a question of what grounds testimonial justification. I also suggest that the hashtag campaign does not simply assert that ‘we should trust women’, but also militates against a pernicious striking-property generic (roughly: ‘women make false sexual assault accusations’), (...) that distorts our evaluation of women’s testimony concerning sexual assault. I conclude #BelieveWomen does not demand that we believe against the evidence, or uncritically, or be more trusting than we have evidential justification to be. Rather, it aims to bring our trust closer to what is merited by the base-rate of reliable testimony from women concerning sexual assault. (shrink)

According to the Behavioral View of consent, consent must be expressed in behavior in order to release someone from a duty. By contrast, the Mental View of consent is that normatively efficacious consent is entirely mental. In previous work, I defended a version of the Behavioral View, according to which normatively efficacious ‘consent always requires public behavior, and this behavior must take the form of communication in the case of high-stakes consent’. In this essay, I respond to two arguments by (...) proponents of the Mental View. First, Larry Alexander, Heidi Hurd and Peter Westen have argued that my view has mistaken implications concerning the culpability of different actors. I counter that my version of the view does not have these implications, as it leaves us free to draw moral and legal distinctions between different offences involving non-consensual behavior. Second, Larry Alexander and Kimberly Ferzan have argued for an analogy between consent and abandonment: on the grounds that the normative power to abandon resides in one’s will, Alexander and Ferzan concludes consent does too. I counter that abandonment requires behavior, and call into question the assumption that the ethics of property have much to teach us about the ethics of sexual consent. (shrink)

Du Bois regarded social reform as a legitimate object for the scientist. He gave a place to non-epistemic values in scientific reasoning and, to counter the effects of scientific racism, he constructed his approach around the belief that scientists must adopt an assumption or scientific hypothesis that African Americans are human. His engagement in scientific research was a way to reform the society in which he lived, which in turn, led him to defend the faithfulness to fact as his conception (...) of scientific objectivity. This essay examines his sophisticated theory of facts, account of the difference between the natural and human sciences, and unique pragmatist theory of truth. (shrink)

This paper has three goals. The first is to defend Tristan Taromino and Erika Lust (or some of their films) from criticisms that Rebecca Whisnant and Hans Maes make of them. Toward that end, I will be arguing against the narrow conceptions that Whisnant and Maes have of what `feminist' pornography must be like. More generally, I hope to show by example why it is important to take pornographic films seriously as films if we're to understand their potential to shape, (...) or mis-shape, socio-sexual norms. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

What Bar-On and Simmons call 'Conceptual Deflationism' is the thesis that truth is a 'thin' concept in the sense that it is not suited to play any explanatory role in our scientific theorizing. One obvious place it might play such a role is in semantics, so disquotationalists have been widely concerned to argued that 'compositional principles', such as -/- (C) A conjunction is true iff its conjuncts are true -/- are ultimately quite trivial and, more generally, that semantic theorists have (...) misconceived the relation between truth, meaning, and logic. This paper argues, to the contrary, that even such simple compositional principles as (C) have substantial content that cannot be captured by deflationist 'proofs' of them. The key thought is that (C) is supposed, among other things, to affirm the truth-functionality of conjunction and that disquotationalists cannot, ultimately, make sense of truth-functionality. -/- This paper is something of a companion to "The Logical Strength of Compositional Principles". (shrink)

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive feat. (...) Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort. (shrink)

A reality for many information technology (IT) organizations is the need to hire IT talent from other cities or countries to supplement their employee staff. As organizations extend their software development work to remote locations, however, a distinct productivity gap can emerge between co-located and distributed teams. The problem this study addresses is the reduced productivity levels for teams practicing the Agile methodology when team members are distributed by location or time zone. Specifically, it was unknown if there are organizational (...) factors which can improve the productivity of these distributed development teams. The purpose of this study was to determine whether any amount of separation of team members impacts productivity, or if various degrees of time zone overlap allows for sufficient synchronous communication to overcome the communication lag inherit with having distributed teams. Productivity was measured by the number of story points per cycle day completed by the team. Two additional variables were collected to study the impact of sourcing and task complexity on distributed team productivity. A quantitative data analysis was conducted on a large, globally distributed technology organization practicing the Agile methodology across the Americas, Europe, Africa, Asia, and Australia. Teams were classified in the study based on the amount of time zone overlap of the team members. The results of the study found that teams which were co-located or had any amount of time zone overlap performed at similar levels of productivity, while teams with no overlapping business day experienced significantly lower levels of productivity (p < .05). Conversely, sourcing of the resources either as contractors or employees did not demonstrate a significant difference in team productivity. The data analysis on task complexity showed mixed results; there was a different level of productivity when some teams were working tasks of different complexity, but the data was further nuanced by team member location. This study indicates the importance of resource location as a key factor in team productivity. Further study on organizational design could be beneficial to better understand how organizations should select locations to optimize productivity. (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...) monitoring and decision-making for stakeholders and policymakers. (shrink)

Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive model (...) achieved an accuracy rate of 78%, shedding light on the underlying patterns within the data. However, this paper underscores the multifaceted nature of survival prediction and acknowledges several challenges. These include missing data imputation, feature engineering, and the inherent noise within historical datasets. We further discuss the importance of model evaluation metrics, showcasing not only accuracy but also precision, recall, and F1-score as essential indicators of predictive performance. The research paper meticulously outlines the architecture of the ANN model, emphasizing the key hyperparameters, activation functions, and regularization techniques employed in model development. Additionally, we address ethical considerations related to data handling and potential biases within the dataset. While our achieved accuracy is a notable achievement, this study emphasizes the importance of interpreting the results with due caution. It underscores the need for a holistic perspective that considers the practical implications of false positives and false negatives, especially in the context of a disaster scenario. In conclusion, this research contributes to our understanding of survival prediction in historical events like the Titanic disaster using modern machine learning techniques. It calls for further exploration and refinement of predictive models, with a focus on enhancing the interpretability and generalizability of such models to real-world applications. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

A teaching document I've used in my courses on truth and on incompleteness. Aimed at students who have a good grasp of basic logic, and decent math skills, it attempts to give them the background they need to understand a proper statement of the classic results due to Gödel and Tarski, and sketches their proofs. Topics covered include the notions of language and theory, the basics of formal syntax and arithmetization, formal arithmetic (Q and PA), representability, diagonalization, and the incompleteness (...) and undefinability theorems. (shrink)

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...) the ITS was done by a group of students and teachers. The results were acceptable. (shrink)

The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery rate (...) was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The research found the following results: there is a fair degree of approval on "cognitive dimension", there is a high approval about the importance of "organizational dimension", there is moderately consent of the importance of "Community dimension", there is a large degree of consent about the importance of axis of the "leadership excellence", there is a large degree of consent about the importance of axis of the "service-excellence", there is a fair degree approval about the importance of the axis of "cognitive excellence", and there is a moderately consent of the importance of "Organizational Excellence". The research found a group of recommendations including: the need to develop appropriate strategies for the University, employ modern technology in information systems, in addition to provide appropriate environment that achieve learning organizations, develop technological infrastructure, adopt universities for knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments, create technological incubators in universities to adopt excellence academic research projects, and protected them, support them, and market them. Establishing of centers of excellence for scientific research in the university.The need for cooperation and coordination between local, Arab and international universities for the exchange of knowledge, information, and participation programs and training courses, as it provides an opportunity to develop the capabilities and skills of personnel and expertise. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

The purpose of this research is to identify the extent of the efficiency of the internal control environment in the Palestinian higher educational institutions in Gaza Strip from the perspective of employees in the Palestinian universities in Gaza Strip, where researchers used in the study five universities. The researchers adopted in their study the descriptive and analytical approach. The research community consists of administrative employees and academic employees with administrative duties. Senior management or the University Council was excluded. The study (...) population compromises of (392) employees. A stratified random sample was chosen and (197) questionnaires were distributed. (160) questionnaires were received back with a return rate of (81.2%).The researchers used a questionnaire to collect that which then was analyzed using (SPSS) to get the results. The research found the following results: the absence of a fundamental difference between the responses of males and females. The lack of significant difference between the responses of the respondents attributed to the variable age. The lack of significant difference between the responses of the respondents attributed to the variable of years of service. And the existence of a fundamental difference between the responses of the respondents attributed to the university variable. The existence of a fundamental difference between the responses of the respondents attributed to the Qualification variable. The existence of a fundamental difference between the responses of the respondents attributed to the administrative level variable. The research found a group of recommendations including: the need to raise awareness of censorship as the basis for the protection of employees in all administrative levels from making mistake.Updating the systems and instructions of control periodically and parallel with the scientific progress and technology.Benefit from regional and international experiences in the application of internal control standards which commensurate with the administrative system of the institution. (shrink)

Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, and (...) other relevant clinical information. The proposed expert system presents an overview about vertigo diseases are given, the cause of disease is outlined and the treatment or recommendation of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. The potential of the proposed expert system lies in its ability to enhance the accuracy and efficiency of vertigo diagnosis, as well as assist in the proper referral and management of patients. (shrink)

This study aims to look at the role of the practice of excellence strategies in education in achieving sustainable competitive advantage for the Higher educational institutions of the faculty of Engineering and Information Technology at Al-Azhar University in Gaza, a model, and the study considered the competitive advantage of educational institutions stems from the impact on the level of each student, employee, and the institution. The study was based on the premise that the development of strategies for excellence in education, (...) and its implementation is a vital important prerequisite to achieve sustainable competitive advantage in higher educational institutions. The study followed a systematic exploratory descriptive methodology through review of the theoretical literature, and the adoption of the experience of the Faculty of Engineering and Information Technology at Al-Azhar University in Gaza as a model for its unique experience in the field of excellence in education. The study results showed that the most important are: There is a strong correlation between the level of exercising excellence strategies in education and the achievement of higher educational institutions to the sustainable competitive advantage. The results include a general required number of important sub results on the subject of the model - Faculty of Engineering and Information Technology at Al-Azhar University in Gaza as follows: - The student considered the academic focus of the operation in the development process of the workers’ skills, particularly academics at the university helps to distinguish students and increase the employment rate after graduation. - The existence of consistency in development efforts and quality improvement for all three levels (student, employee, and the university), and this contributes to the Faculty excellence. - The Faculty has been able to achieve competitive advantages by offering excellent services without harming the efficiency, and this alone is a great success because improving service properties requires great investments, which negatively affect the continued institutional development. The study also reached a set of recommendations as follows: - The need to exercise excellence strategies in education, excellence reward at the national level, and those higher educational institutions follow the criteria for measuring the competitive advantages of its institutions always. - There is a need to increase efforts to implement programs of excellence, the allocation of adequate time, reward outstanding efforts as well. There is a necessity for each faculty to achieve competitive advantage and sustainability, using the general philosophies of competitive advantage, but with a different strategically content from what is in the private commercial sector, it reflects the Faculties mission and objectives, depending on making improvements and excellence in processes that ensure the safety of its outputs. As well as the need to find a balance between the work of teaching and research work of the faculty members, this has important implications regarding the criteria used in the process of excellence evaluation. The study recommended the adoption of strategies for excellence in education on a national public policy level mainly in the processes of change in higher education institutions. The need to support the existence of a common understanding of the efforts of excellence to create a general culture that appreciates excellence in faculties and universities. This underlines the need for transparent, fair rewards systems, to encourage innovation in education. The need to conduct a comprehensive surveys on the graduates of faculties and universities including the areas of employment and skills, because that will give accurate indications of the graduates and will help to establish a link to a more precise about the relationship of excellence strategies with the competitive advantages. (shrink)

It has been known for some time that context-dependence poses a problem for disquotationalism, but the problem has largely been regarded as one of detail: one that will be solved by the right sort of cleverness. I argue here that the problem is one of principle and that extant solutions, which are based upon the notion of translation, cannot succeed.

The research aims to identify the reality of modern methods applied in the process of performance assessments of employees in the municipalities of Gaza-strip, Complete Census method of community study was used, (571) questionnaires were distributed to all members of the community study, (524) questionnaires were recovery with rate of (91.76%). The most important findings of the study: There were statistically significant relationship differences between the applications of modern methods in the performance assessments of employees in the municipalities of Gaza-strip. (...) There was statistically significant relationship between the evaluation criteria that fit the required performance and the application of standards evaluations on performance of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the use of methods, models for the evaluation of appropriate functions and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the feedback and the application of performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the efficient, professional assessors and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the extent of awareness of subordinates, participation in the evaluation of their performance and the application of the performance assessments of employees in the municipalities of Gaza-strip. The research also concluded a series of recommendations, including: that the design of evaluation models must be done with the participation of the employees and inform them of it, and that a date must be set to provide feedback and discuss the results with them, that they should be allowed grievance in front of an ad hoc committee in accordance with the known system. Direct manager must inform employees of their performance assessment date, discuss the results of the evaluation with them, and others should be involved with the direct manager of employees in their performance evaluation. The application of modern methods of performance evaluation through the good and purposeful planning should be used, analyzing and employing the results in administrative decisions regarding the employees, and the application of modern methods must be used in an effective and efficient performance evaluation. (shrink)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...) used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...) specifically using the pre-trained model on top of the VGG16 architecture. Then, dense layers were added to classify the output of the Convolutional layers and classify outputs to the five classes (species) the leaf belonged to. Results: It was found that feature extraction without fine-tuning the convolutional layers yielded poor results, about 86% accuracy, while training the whole network along with some data preprocessing gave the best results, about 99.45% accuracy on the testing dataset. Conclusions: The proposed CNN model is an effective one for the problem of classification of grape leaf species. (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to the (...) field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging represents a transformative shift in healthcare, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. This paper explores the application of AI technologies in the analysis of medical images, focusing on techniques such as convolutional neural networks (CNNs) and deep learning models. We discuss how these technologies are applied to various imaging modalities, including X-rays, MRIs, and CT scans, to enhance disease detection, image segmentation, and diagnostic support. Additionally, the (...) paper addresses the challenges faced in AI-driven medical imaging, including data quality, model interpretability, and ethical considerations. By examining recent advancements and real-world case studies, this paper provides insights into the current state of AI in medical imaging and its potential future directions. The findings highlight the ongoing evolution of AI technologies and their crucial role in advancing medical diagnostics and treatment strategies. (shrink)

Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations. (shrink)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to enhance (...) model generalizability. (shrink)

Critics have recently argued that reliabilists face trade-off problems, forcing them to condone intuitively unjustified beliefs when they generate lots of true belief further downstream. What these critics overlook is that reliabilism entails that there areside-constraintson belief-formation, on account of which there are some things you should not believe, even if doing so would have very good epistemic consequences. However, we argue that by embracing side-constraints the reliabilist faces a dilemma: she can either hold on to reliabilism, and with it (...) aforementioned side-constraints, but then needs to explain why we should allow the pursuit of justification to get in the way of the acquisition of true belief; or she can deny that there are side-constraints – and in effect give up on reliabilism. We'll suggest that anyone moved by the considerations that likely attract people to reliabilism in the first place – the idea the true belief is good, and as such should be promoted – should go for the second horn, and instead pursue a form ofepistemic utilitarianism. (shrink)

Family members can provide crucial support to individuals participating in clinical trials. In research on the “newest frontier” of Deep Brain Stimulation (DBS)—the use of DBS for psychiatric conditions—family member support is frequently listed as a criterion for trial enrollment. Despite the significance of family members, qualitative ethics research on DBS for psychiatric conditions has focused almost exclusively on the perspectives and experiences of DBS recipients. This qualitative study is one of the first to include both DBS recipients and their (...) family members as interview participants. Using dyadic thematic analysis—an approach that takes both the individuals and the relationship as units of analyses—this study analyzes the complex ways in which family relationships can affect DBS trial participation, and how DBS trial participation in turn influences family relationships. Based on these findings, we propose ways to improve study designs to better take family relationships into account, and better support family members in taking on the complex, essential roles that they play in DBS trials for psychiatric conditions. (shrink)

Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which utilizes (...) rule-based techniques to analyze symptoms associated with mango pests. By inputting observed symptoms, such as leaf spots, fruit damage, leaf mild and stem cankers the system can accurately identify the specific pest species affecting the mango tree. For each pest, the paper discusses their specific symptoms and Favorable conditions that affect the mango plant. By understanding the identification and symptoms of these pests, mango growers and agricultural professionals can implement appropriate pest management strategies to mitigate the economic losses caused by these insects. The research presented in this paper aims to contribute to the body of knowledge on mango pest management, facilitating sustainable mango production and ensuring the availability of high-quality mangoes in global markets. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence that (...) cognitive influences in the visual system produce neural reorganization in the primary visual cortex. The type of cognitive penetration can be synchronic and diachronic. (shrink)