Biggest Value Research Articles

Back-propagating errors through artificial neural networks for variable selection

Variable selection is one of the most important contents of machine learning research and a large number of variable selection methods have been proposed at present. From deep learning perspective, we propose a new variable selection method based on multi-layer artificial neural networks in this paper. The method propagates errors gained form a trained network model through the network from output layer to input layer and the values gained by input layer give information about the relative contribution. The variables with big contribution value are selected, which we call neural inverse propagation (NIP). Specifically, after training a neural network, the gained errors between the actual network outputs and the desired outputs go through the network from top to down and arrive at the input layer. The absolute values gained by input units provide information about the relative importance (contribution) of input units, which is that the larger the value is, the more important the corresponding input variable is. We remove k variables corresponding to the first k minimum absolute value gained by input units to the predictive variables, to perform variable selection. The efficiency of the proposed method is illustrated through its application to classification and regression tasks on a number of synthetic datasets and a real-world image classification dataset.

Breast Ultrasound Images Augmentation and Segmentation Using GAN with Identity Block and Modified U-Net 3.

One of the most prevalent diseases affecting women in recent years is breast cancer. Early breast cancer detection can help in the treatment, lower the infection risk, and worsen the results. This paper presents a hybrid approach for augmentation and segmenting breast cancer. The framework contains two main stages: augmentation and segmentation of ultrasound images. The augmentation of the ultrasounds is applied using generative adversarial networks (GAN) with nonlinear identity block, label smoothing, and a new loss function. The segmentation of the ultrasounds applied a modified U-Net 3+. The hybrid approach achieves efficient results in the segmentation and augmentation steps compared with the other available methods for the same task. The modified version of the GAN with the nonlinear identity block overcomes different types of modified GAN in the ultrasound augmentation process, such as speckle GAN, UltraGAN, and deep convolutional GAN. The modified U-Net 3+ also overcomes the different architectures of U-Nets in the segmentation process. The GAN with nonlinear identity blocks achieved an inception score of 14.32 and a Fréchet inception distance of 41.86 in the augmenting process. The GAN with identity achieves a smaller value in Fréchet inception distance (FID) and a bigger value in inception score; these results prove the model's efficiency compared with other versions of GAN in the augmentation process. The modified U-Net 3+ architecture achieved a Dice Score of 95.49% and an Accuracy of 95.67%.

Penetrasi Nilai-Nilai Kepemimpinan Bigman dalam Pemerintahan Kampung di Kabupaten Manokwari Selatan

The overall objective of the research is to identify the penetration of bigman leadership values in village governance in Oransbari District, South Manokwari Regency. This research uses an exploratory paradigm, a descriptive approach with qualitative research (in-depth interviews). The data collection methods used were observation, interviews and documentation. Data analysis follows the procedures of data collection, data presentation and drawing conclusions. The results of these findings show that the penetration of big man leadership values in village governance in Masabui one Masabui two Watariri villages is still controlled by traditional values, especially the value of power and ownership of customary rights and rights as a tribal chief, which are used in governance starting from the leader. The village structure prioritises the values of responsibility and transparency, even though it is controlled by a patrilineal family. The penetration of bigman leadership values in village governance in Oransbari District, South Manokwari Regency, has had a very strong influence. This influence is due to the power system of the tribal chief as the holder of customary rights, which has become a customary provision that all organisations entering the village must be headed by the holder of customary rights, who is also the local tribal chief, including bodies in the organisational structure, because it has become customary. As a legacy from generation to generation, all the trust of the community will be directed towards him. In addition, as the head of the village, the tribal chief plays an important role and is fully responsible for all government programmes that come to the village. He is also responsible for solving all problems related to violations and disputes in the village.

Big Data Features As Crucial Concept which Effects Data Interoperability

Big data has become an exciting term in the last decades, and it conducts a significant rate of data with different features of velocity, variety, value, volume, and veracity. Those features describe big data identity. Think about the data generated by social media websites and apps, such as Facebook, Twitter, and WhatsApp…...Etc. This data is crucial because of the amount, variety, and growth acceleration, but it is exhausting to manage. Big data interoperability indicates the capability to interchange and share the data, information, and knowledge between organizations and devices that knowledge and information were extracted from different data sources. This complex mutual process grows an organization's performance. According to the previous, big data and its five features are essential because of its usability and analytics. Organizations need to extract the expected benefit from preserving and retrieving data. We develop a data interoperability concept, which is improved as data exchangeability can be enriched. In this study, we will discuss the impact of big data feature's value, volume, variety, velocity, and veracity on the interoperability of the data and data exchangeability feasibility and how these features affect the prediction of future decisions in the institution, as well as the interaction and exchange of data between the organizations.

Experimental Study on Seismic Response of Underground Tunnel–Soil–Piled Structure Interaction Using Shaking Table in Loose Sand

The seismic response of structures can have a significant impact on adjacent structures’ response. Although several numerical studies have been applied in the field of tunnel–soil–pile interaction systems, there is a lack of experimental research specifically focused on the effects of this interaction on tunnel cross-section deformation and the existence of structure on encircling soil response. In this study, shaking table tests were conducted to examine the seismic response of a tunnel and the surrounding soil when an eight-story structure with piles was located in the vicinity of the tunnel. Four series of physical models were analyzed, including free-field soil (S), tunnel–soil (TS), soil-piled structure (SP), and tunnel–soil-piled structure (TSP), under sinusoidal vibration at three frequencies on loose sand. According to the results, the tunnel significantly impacts the surrounding soil response during seismic excitation with reduced acceleration at the tunnel invert and increased acceleration at the tunnel crown. In the TSP model, applied frequency affects the recorded acceleration amplitude at the tunnel invert. Although acceleration amplitude decreases at 3 Hz frequency excitation compared to the free field model, 8 Hz excitation resulted in bigger values in tunnel invert. Displacements are higher at the tunnel crown, indicating tunnel-induced soil deformation and maximum shear strain concentrated near the tunnel crown. The tunnel cross-section exhibited oval shape changes, with higher forces on the tunnel crown in the presence of piles.

Teacher personality domains and facets: Their unique associations with student-ratings of teaching quality and teacher enthusiasm

BackgroundPrevious research on the relationship between teacher personality and teaching performance yielded mixed results and typically considered only the broad personality domains while neglecting the narrower personality facets that constitute the domains. AimThe aim of this study was to examine the incremental value of teacher Big Five personality facets in explaining student-ratings of teaching quality and teacher enthusiasm. SamplesIn total, 1067 teachers and 18,814 of their students from 73 secondary schools in Croatia participated in the study. MethodTeachers self-reported their personality whereas students rated the teaching quality and displayed enthusiasm of their teachers. Each teacher was rated by one class of students. ResultsThe bifactor-(S-1) multilevel structural equation models for each Big Five personality domain showed that both the general reference factor and the specific factors explained the variance in student-ratings of teaching quality and teacher enthusiasm. ConclusionsA more fine-grained approach to examining the effects of teacher personality at different levels of hierarchy might be helpful for identifying specific parts of teacher personality with the greatest explanatory power in predicting teaching performance.

Big Data Management and Analytics as a Cloud Service

Traditional database management systems are inadequate for handling uncertain data due to design limitations. Various methods address database uncertainty, often oversimplifying and restricting representable uncertainties. Rapid data growth from technologies like IoT, multimedia, and social media has led to massive diverse data, known as big data, categorized into structured, semi-structured, and unstructured types. Coping with big data's challenges is encapsulated in the "Vs Model" with volume, velocity, and variety dimensions. It aims to gather variable information for causal understanding and informed decisions. Big data offers competitive advantages: smart decisions (69%), operational control (54%), customer insights (52%), and cost cuts (47%). This research studies big data management and cloud computing, where data and apps are accessed via the internet, saving resources globally. Cloud's simplicity and power facilitate tasks and storage. Risks include bankruptcy or breaches, yet cloud remains valuable for preserving big data. Vital factors in big data's value creation involve converting IT costs to assets and connecting big data outcomes to performance. This abstract summarizes exploration of traditional limitations, big data's essence, cloud's potential, and value creation nuances.

Grazing Decreases Soil Aggregation and Has Different Effects on Soil Organic Carbon Storage across Different Grassland Types in Northern Xinjiang, China

Soil aggregates, as the basic component of soil, make great contributions to the stability of soil structure and soil carbon (C) sequestration. Recently, grasslands have been experiencing continuous grazing, which has had a significant impact on soil aggregation and soil C storage. However, how soil aggregates and soil C in different grasslands respond to grazing remains unclear. Therefore, three national fenced grassland-monitoring sites that represented mountain meadow (MM), temperate steppe (TS), and temperate steppe desert (TSD) were selected to investigate the differences in the responses of soil aggregates and soil C among grazing of different types of grasslands. Soil samples of 0–10 cm was collected from both inside and outside the fence of each site to analyze soil properties and soil aggregate characteristics. The results showed that soil nutrients varied greatly among the three grassland types, with the highest values in MM. At each site, grazing increased the content of sand and decreased the contents of silt and clay compared to fenced plots. Soil aggregate composition showed significant responses to both grassland type and grazing, especially the proportions of soil aggregates >2 mm, which significantly decreased by 51.7% on average in grazing plots compared with fenced plots. A significant decrease (on average, 25.1%) in the mean weight diameter (MWD) of soil aggregates under grazing was detected across all grassland types. The effect of grazing on nutrients in macroaggregates (>0.25 mm) was greater than that in microaggregates (<0.25 mm). Aggregate-associated SOC concentration decreased under grazing in MM and TS. However, grazing had no significant influence on the SOC density of MM, while it led to a significant decrease in TS and an increase in TSD. The magnitude of grazing effect size on aggregate-associated SOC varied with different soil particle sizes, with greater responses in aggregates >2 mm and the biggest value in TDS. In addition, the results of the correlation analysis and redundancy analysis (PDA) indicated that soil bulk density and nutrients made the main contribution to soil composition and stability of soil aggregates. Overall, grazing had a significant influence on soil aggregation, stability, and SOC, playing a crucial role in grassland soil stability and the accumulation of SOC.

CoReS: Compatible Representations via Stationarity.

Compatible features enable the direct comparison of old and new learned features allowing to use them interchangeably over time. In visual search systems, this eliminates the need to extract new features from the gallery-set when the representation model is upgraded with novel data. This has a big value in real applications as re-indexing the gallery-set can be computationally expensive when the gallery-set is large, or even infeasible due to privacy or other concerns of the application. In this paper, we propose CoReS, a new training procedure to learn representations that are compatible with those previously learned, grounding on the stationarity of the features as provided by fixed classifiers based on polytopes. With this solution, classes are maximally separated in the representation space and maintain their spatial configuration stationary as new classes are added, so that there is no need to learn any mappings between representations nor to impose pairwise training with the previously learned model. We demonstrate that our training procedure largely outperforms the current state of the art and is particularly effective in the case of multiple upgrades of the training-set, which is the typical case in real applications.

Numerical analysis of the heat transfer enhancement by using metal foam

Forced convection heat transfer in metal foam pipe under uniform heat flux was investigated numerically. Water has been used as the fluid medium in numerical simulations with copper metal foam. The test sample used metal foam for four cases (A, B, C, and D) by using varying thicknesses of foam along the pipe. In case (A), the pipe was completely filled with metal foam; in case (B), the pipe was partially embedded with metal foam and close to the wall; in case (C), the pipe was partially filled in the section's center; and in case (D), the pipe was partially filled in the form of three sections along the pipe. The foam employed in this study has a porosity of 0.90 and pore density ranges from (10–40) PPI. The fluid and energy transfers are simulated using the Forchheimer-extended Darcy equation and the local thermal non-equilibrium (LTNE) model. The simulation is performed using the commercial software FLUENT with specific boundary conditions. Turbulence was taken into account using the k- ε model. The results reveal that when the pipe is filled partially with metallic foam as indicated in case B, the Nusselt ratio rises due to the velocity gradient and temperature distribution is more homogenous inside the pipe led to enhancement in overall heat transfer. Also, the metallic foam 40PPI has a highly Nusselt number ratio, with a big value equal to 5.5 in case B due to the highly conductive surface area of heat transfer from the wall heated to the fluid. Additionally, the pipe in case A was completely filled with metallic foam, resulting in a bigger pressure drop than in the other cases, which increases flow resistance. The metal foam in case C, which is centered in the pipe's center, has the lowest pressure drop measurement. The 10PPI metallic foam exhibits the highest performance factor when compared to other metallic foam.

Fixed Points and λ-Weak Contractions

In this paper, we introduce a new type of contractions on a metric space (X,d) in which the distance d(x,y) is replaced with a function, depending on a parameter λ, that is not symmetric in general. This function generalizes the usual case when λ=1/2 and can take bigger values than m1/2. We call these new types of contractions λ-weak contractions and we provide some of their properties. Moreover, we investigate cases when these contractions are Picard operators.

Scientific concept and practices of life community of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts in China.

China prioritizes ecological civilization construction and embraces the concept of "lucid waters and lush mountains are invaluable assets." Great achievements have been made in ecological protection and restoration through implementing a series of policies and projects. This paper reviews the history of ecological restoration in China and the current development of the "integrated protection and restoration project of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts (IPRP)." Furthermore, the characteristics of IPRP were systematically elaborated from the perspectives of the ecological civilization thought, the policy management, and the key scientific issues. Also, the current achievements were summarized in the fields of national ecological space management, biodiversity conservation, and ecological protection and restoration. Existing challenges in management policy, scientific issues, and engineering practices were highlighted. Future perspectives include ecological space control, nature-based Solutions, biodiversity big data platform, modern techniques, and value realization mechanisms of ecological products.

The Governance of Big Data and Artificial Intelligence in Network Industries

An important precondition for the development of artificial intelligence (AI) in network industries is the access to big data and the attendant necessities of data sharing and data portability. The goal of this paper is to analyze the changing needs of entrepreneurial decision-making to exhaust the innovation potential of AI-driven big data value chains taking into account AI-specific ethical, security and privacy regulations. The analytical concept of AI-powered big data virtual networks is investigated with a focus on the governance of 5G-based big data value chains required for Internet of Things (IoT) applications in particular smart networks. Although several actors may be involved—such as broadband providers, cloud service providers, geopositioning service providers, or sensor network service providers—the final responsibility for bundling these different service components lies in the hands of the AI-powered big data virtual network providers. In addition to the required data privacy and security regulations, the exploration of new liability rules for AI interacting with traditional technologies is becoming relevant, taking into account AI-specific ethical and transparency obligations. Firstly, the complementary roles of the EU data regulatory framework and European AI regulatory framework are examined. Secondly, the network economic concept of AI-powered big data virtual networks is elaborated taking into account the required regulations. Thirdly, the heterogeneity of AI systems—required for a variety of IoT applications—is considered, with a particular focus on the application of AI within the transportation sector.

Sistem Pendukung Keputusan Pengembangan Ekowisata Mangrove Potensial Menggunakan Simple Additive Weighting (SAW)

Adjusting resource availability and traveler preferences will allow for an objective assessment of prospective mangrove ecotourism growth. In order to build mangrove ecotourism destinations effectively, it is vital to identify their priority locations. It is required to create the development program as a criterion and the development zone as a prioritized alternative in light of this. This study used the Simple Additive Weighting (SAW) technique, which includes the following stages: deciding on criteria and alternatives; weighing the relative importance of each criterion; creating a matrix of findings; and ranking the alternatives based on the biggest value. The study's findings indicate that five criteria can be categorized based on benefit and cost with varying relative values: attraction (benefit), ancillary (benefit), accommodation (cost), accessibility (cost), and amenities (cost). Attraction has a relative value of 0.3, ancillary has a relative value of 0.2, and amenities (cost) has a relative value of 0.15. The ranking results showed that the amenity criteria came first, followed by accessibility, then attractions, lodging, and ancillary. Attractions were ranked third, while accommodations came in fourth. This demonstrates the necessity for amenities that pique tourist interest and accessibility through accessible modes of transportation, informational resources, and roads to tourist destinations to support the growth of mangrove ecotourism special interest tourism. The management of mangrove ecotourism destinations can be improved by offering lodging options. Following amenities, accessibility, attractions, and lodging, organizations or groups can be established, and infrastructure in tourist sites can be enhanced. As a result, the SAW approach can be used as a system to help decide which initiatives to prioritize

New challenges for public value and accountability in the age of big data: a bibliometric analysis

PurposeThis paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation of public value. This paper presents a map of current knowledge in a sample of selected articles and explores the intersecting points between data from the private sector and the public dimension in relation to benefits for society.Design/methodology/approachA bibliometric analysis was performed to provide a retrospective review of published content in the past decade in the field of big data for the public interest. This paper describes citation patterns, key topics and publication trends.FindingsThe findings indicate a propensity in the current literature to deal with the issue of data value creation in the private dimension (data as input to improve business performance or customer relations). Research on data for the public good has so far been underestimated. Evidence shows that big data value creation is closely associated with a collective process in which multiple levels of interaction and data sharing develop between both private and public actors in data ecosystems that pose new challenges for accountability and legitimation processes.Research limitations/implicationsThe bibliometric method focuses on academic papers. This paper does not include conference proceedings, books or book chapters. Consequently, a part of the existing literature was excluded from the investigation and further empirical research is required to validate some of the proposed theoretical assumptions.Originality/valueAlthough this paper presents the main contents of previous studies, it highlights the need to systematize data-driven private practices for public purposes. This paper offers insights to better understand these processes from a public management perspective.

Experiment Measurement of the Dry Density Variations and Shear Stress with the Different Depth Variations

Evaluation of the dry density variations and shear stress with the different depth variations were shown clearly with the particular process. Results show the Dry unit weight (density) increases gradually with the increase of different depths. The biggest dry density was obtained at 1.582 g/cm3 at 18.3m depth of boreholes (“HK1, 2, and 3”); whereas the lowest value was obtained at 0.74 g/cm3 at 4.3m depth. On the other hand, the dry density changed with the constant loading process. The biggest dry density is 1.954 g/cm3 at 18.3m depth and the lowest value is 1.482 g/cm3 at 8.3m depth (before loading); The biggest value is 2.074 g/cm3 at 18.3m depth and the lowest value is 1.621 g/cm3 at 8.3m depth (after loading). Moreover, shear stress was measured carefully at different depths. At the Clay layer, the lowest value is τ1 with 0.052 kG/cm2 at 4.8m depth; whereas the biggest is τ3 with 1.750 kG/cm2 at 39.6m depth. The biggest value is τ2 with 1.276 kG/cm2 at 17.8m depth. At the Sand layer, the lowest value is τ1 with 0.586 kG/cm2 at 29.8m depth; whereas the biggest is τ3 with 1.750 kG/cm2 at 39.6m depth and τ2 with 1.21 kG/cm2 at 36.0m depth.

Handover Between Prehospital and Intra-hospital Physicians–Utility of Simulation in Enhancing Quality of Transmission

Introduction:Handover is of big value in preserving continuity of the medical services chain when managing patients. Simulation is well accepted as a good learning method to acquire non-technical skills. Actual studies dealing with this issue are performed on paramedics. Studies involving physicians are rare and usually focus on interviews or questionnaires describing practical situations.The aim of our study was to evaluate the utility of simulation in enhancing the quality of handover between both pre-hospital and intra-hospital physicians.Method:We conducted a prospective pre-test/post-test study in a regional Emergency Medical System (EMS) on the handover topic.We included voluntary physicians who signed participation consent. The study was designed as a three-step project: theoretical training with pre-test and post-test, 1st simulation session, 2nd simulation session with post-test. The two simulation sessions were evaluated according to a specific score. We evaluated the progression of knowledge (tests means) and skills (percentages of good answers): before and after theoretical training and before and after simulation sessions.Results:Sixteen EMS physicians were enrolled. Thirteen were under 40 years old and ten were emergency medicine physician specialists. Theoretical training made progression in means and percentage good answers (post-test 1 vs. pré-test : 9.5±3.3 vs 6.9±2 ; p=0.008 et 22 vs. 10% ; p=0,001 respectively). Progression of means after simulation was noticed (2nd session vs. 1st session) (16.3±0.9 vs. 12.3±2.5 ; p<0.001). Simulation enhanced significant quality of handover. Means and percentage of good answers in tests was better after simulation sessions (post-test 2 vs. post-test 1 vs. pre-test : 10.7±2.8 vs. 9.5±3.3 vs. 6.9±2 ; p=0.01 et 29% vs. 22% vs. 10% ; p<0.001 respectively).Conclusion:Our study showed the utility of simulation in enhancing handover between pre-hospital and intra-hospital physicians. Simulation as an active learning method, combined with theoretical training, can improve knowledge and enhance skills.

MATHEMATICAL EXPRESSIONS FOR TEMPERATURE IN THE CONTACT ZONE OF TEETH OF THE GEAR MECHANISMS

Transmission gears are very widely used in modern machine building. Despite that electrical transmissions used in machine building industry, mainly mechanical transmissions are widely used in the industry. Because mechanical transmissions are independent and better than other transmisions. Distributing power between the transmission mechanisms and working units of various machines, changing the angle of momentum, by adjusting the speed of the parts, it is possible to change the type of movement, turn on and off the mechanism, change the direction of the transmission mechanisms. One of the most widespread types of transmission technology is the gear transmission. Tens of thousands of kilowatt-hours of gears can be transmitted. Advantages of gear transmission in comparison with others is their ability to maintain their reliability and long term functioning of the teeth, big value of the working coefficient (0,9 ÷ 0,99), simple construction, lack of special service, simplicity of the transmission number and compactness of dimensions. The missing aspects of these transmissions are high precision in their preparation and installation, and low noise level. The main criterion for the working ability of the closed gear transmissions is the contact endurance of the active surface of the tooth. For this reason, the main dimensions of the transmission are determined by the contact tension and by teeth bending. Keywords: gear wheel, tension, endurance, bending

OPTIMASI PARAMETER 3D PRINTING TERHADAP WAKTU DAN WARPING DENGAN PENDEKATAN METODE TAGUCHI

Fused Deposition Modeling (FDM) is one of the most popular 3D printing technology that used at academic and business purposes due to the easiness of the manufacture process that it held. But, one of the most major problems that usually occur in the industry is the frequentness of damaged and deficiency on the result of printing, especially when it is printed using the ABS filament. Although, ABS is one of the filaments which has a lower cost compared to others, but has a bigger value per gram on the printing sectors compared to PLA filaments. It could be a good business prospect if it can be handled on the problems. Therefore, the knowledge on how to prevent the problems, and finding an efficiency on the various of infill pattern, would be one of the key of success in this industry. In this article, a research on finding optimum parameters against the time and quality of the product using the Taguchi method, and also ASTM D-638 is also needed to find the best infill pattern against the tensile strength that an ABS filament have on the mechanical properties. As a result, the parameters, nozzle temperature and bed temperature have a small impact on producing time, but have a greater impact on the quality of printing product. Besides, the infill pattern which has the biggest tensile strength on smaller density is Trihexagon. Meanwhile, the Lines infill has the biggest standard of deviation, which endure the most stress on the bigger density compared to Triangles and Trihexagon.

Comparison of Task Specific Training Vs Neuro Developmental Training Approach Along with Conventional Therapy for Upper Limb Motor Function Among Chronic Stroke Patients

Objective The purpose of the study is to determine the effect of Proprioceptive Neuromuscular Facilitation Vs Balance Exercise along with Conventional Therapy for balance and gait in Chronic Parkinson’s patients. Study Design Randomized Controlled Trial (RCT). Place and Duration of study This study took place in Lahore, Pakistan and the duration of the study was 6 months. Method This study is a Randomized Controlled Trial utilized a non-probability purposive sampling technique, the primary outcome measure was Berg Balance Scale and Functional Gait Assessment which were used to check the balance and gait. The findings were then statistically analysed by non parametric tests Mann Whitney U Test and Friedman Test were used for between group and within the group comparisons respectively. Results A total of 60 patients participated in the study among which after randomized allocation of 30(50%) in PNF group and 30(50%) in Balance T group. The data shows that there is a big difference mean value difference between the two groups i.e. Balance T group showed better results than the PNF group and the p value is 0.000 which is less than 0.05 hence suggesting that the difference between both the experimental the groups after 12 weeks is highly significant. Hence we are rejecting the Null hypothesis and accepting the alternating hypothesis. . The data shows that there is a difference mean value difference between the two groups i.e. Balance T group showed better results than the PNF group and the p value is 0.492 which is more than 0.05 hence suggesting that the difference between both the experimental the groups after 12 weeks is non-significant. Hence we are rejecting the Alternate Hypothesis and accepting the Null Hypothesis. Conclusion Both of the treatment approaches have proven to be effective in treatment of balance of lower limb among chronic Parkinson’s patients but the Balance Exercises has proven to be significantly more effective than of Proprioceptive Neuromuscular Facilitation and show effective results in the treatment of balance more efficiently but among two of these treatment strategies none of them has been proven to be better than other for gait. Discussion In the current study where PNF and Balance exercise are compared to each other shows that Balance exercise is highly effective for the treatment of balance in chronic Parkinson’s patients as compared to PNF. However Del Carmen et.al. Conducted a research in 2019 i.e. “the development of ballet exercises with Proprioceptive Neuromuscular Facilitation techniques for patients with Parkinson’s disease” which indicated that of Proprioceptive Neuromuscular Facilitation technique also improve balance and gait in Parkinson’s disease patients [1].